e%%semi-supervised learning
@article{robbins1951stochastic,
  title={A stochastic approximation method},
  author={Robbins, Herbert and Monro, Sutton},
  journal={The annals of mathematical statistics},
  pages={400--407},
  year={1951},
  publisher={JSTOR}
}


@article{krenn2020self,
  title={Self-referencing embedded strings (SELFIES): A 100\% robust molecular string representation},
  author={Krenn, Mario and H{\"a}se, Florian and Nigam, AkshatKumar and Friederich, Pascal and Aspuru-Guzik, Alan},
  journal={Machine Learning: Science and Technology},
  volume={1},
  number={4},
  pages={045024},
  year={2020},
  publisher={IOP Publishing}
}

@article{grathwohl2019your,
  title={Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One},
  author={Grathwohl, Will and Wang, Kuan-Chieh and Jacobsen, J{\"o}rn-Henrik and Duvenaud, David and Norouzi, Mohammad and Swersky, Kevin},
  journal={arXiv preprint arXiv:1912.03263},
  year={2019}
}

@article{nie2021controllable,
  title={Controllable and compositional generation with latent-space energy-based models},
  author={Nie, Weili and Vahdat, Arash and Anandkumar, Anima},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={13497--13510},
  year={2021}
}

@article{nigam2020augmenting,
  title={Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space},
  author={Nigam, AkshatKumar and Friederich, Pascal and Krenn, Mario and Aspuru-Guzik, Al{\'a}n},
  journal={ICLR 2020},
  year={2020}
}

@inproceedings{
    xie2021mars,
    title={MARS: Markov Molecular Sampling for Multi-objective Drug Discovery},
    author={Yutong Xie and Chence Shi and Hao Zhou and Yuwei Yang and Weinan Zhang and Yong Yu and Lei Li},
    booktitle={International Conference on Learning Representations},
    year={2021},
    url={https://openreview.net/forum?id=kHSu4ebxFXY}
}

@article{de2018molgan,
  title={MolGAN: An implicit generative model for small molecular graphs},
  author={De Cao, Nicola and Kipf, Thomas},
  journal={arXiv preprint arXiv:1805.11973},
  year={2018}
}

@article{zhou2019optimization,
  title={Optimization of molecules via deep reinforcement learning},
  author={Zhou, Zhenpeng and Kearnes, Steven and Li, Li and Zare, Richard N and Riley, Patrick},
  journal={Scientific reports},
  volume={9},
  number={1},
  pages={1--10},
  year={2019},
  publisher={Nature Publishing Group}
}

@article{winter2019efficient,
  title={Efficient multi-objective molecular optimization in a continuous latent space},
  author={Winter, Robin and Montanari, Floriane and Steffen, Andreas and Briem, Hans and No{\'e}, Frank and Clevert, Djork-Arn{\'e}},
  journal={Chemical science},
  volume={10},
  number={34},
  pages={8016--8024},
  year={2019},
  publisher={Royal Society of Chemistry}
}

@inproceedings{luo2021graphdf,
  title={Graphdf: A discrete flow model for molecular graph generation},
  author={Luo, Youzhi and Yan, Keqiang and Ji, Shuiwang},
  booktitle={International Conference on Machine Learning},
  pages={7192--7203},
  year={2021},
  organization={PMLR}
}

@article{polishchuk2013estimation,
  title={Estimation of the size of drug-like chemical space based on GDB-17 data},
  author={Polishchuk, Pavel G and Madzhidov, Timur I and Varnek, Alexandre},
  journal={Journal of computer-aided molecular design},
  volume={27},
  number={8},
  pages={675--679},
  year={2013},
  publisher={Springer}
}

@article{santos2021accelerating,
  title={Accelerating AutoDock4 with GPUs and gradient-based local search},
  author={Santos-Martins, Diogo and Solis-Vasquez, Leonardo and Tillack, Andreas F and Sanner, Michel F and Koch, Andreas and Forli, Stefano},
  journal={Journal of chemical theory and computation},
  volume={17},
  number={2},
  pages={1060--1073},
  year={2021},
  publisher={ACS Publications}
}

@inproceedings{berthelot2019mixmatch,
  title={Mixmatch: A holistic approach to semi-supervised learning},
  author={Berthelot, David and Carlini, Nicholas and Goodfellow, Ian and Papernot, Nicolas and Oliver, Avital and Raffel, Colin A},
  booktitle={Advances in Neural Information Processing Systems},
  pages={5049--5059},
  year={2019}
}


@article{sohn2020fixmatch,
  title={Fixmatch: Simplifying semi-supervised learning with consistency and confidence},
  author={Sohn, Kihyuk and Berthelot, David and Li, Chun-Liang and Zhang, Zizhao and Carlini, Nicholas and Cubuk, Ekin D and Kurakin, Alex and Zhang, Han and Raffel, Colin},
  journal={arXiv preprint arXiv:2001.07685},
  year={2020}
}


@article{atanov2019semi,
  title={Semi-conditional normalizing flows for semi-supervised learning},
  author={Atanov, Andrei and Volokhova, Alexandra and Ashukha, Arsenii and Sosnovik, Ivan and Vetrov, Dmitry},
  journal={arXiv preprint arXiv:1905.00505},
  year={2019}
}


@article{zhaojoint,
  title={Joint Energy-Based Models for Semi-Supervised Classification},
  author={Zhao, Stephen and Jacobsen, J{\"o}rn-Henrik and Grathwohl, Will}
}

@inproceedings{gao2020flow,
  title={Flow contrastive estimation of energy-based models},
  author={Gao, Ruiqi and Nijkamp, Erik and Kingma, Diederik P and Xu, Zhen and Dai, Andrew M and Wu, Ying Nian},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={7518--7528},
  year={2020}
}


@inproceedings{dai2017good,
  title={Good semi-supervised learning that requires a bad gan},
  author={Dai, Zihang and Yang, Zhilin and Yang, Fan and Cohen, William W and Salakhutdinov, Russ R},
  booktitle={Advances in neural information processing systems},
  pages={6510--6520},
  year={2017}
}


%% Molecule
@article{pang2020learning,
  title={Learning Latent Space Energy-Based Prior Model},
  author={Pang, Bo and Han, Tian and Nijkamp, Erik and Zhu, Song-Chun and Wu, Ying Nian},
  journal={arXiv preprint arXiv:2006.08205},
  year={2020}
}

@inproceedings{you2018graph,
  title={Graph convolutional policy network for goal-directed molecular graph generation},
  author={You, Jiaxuan and Liu, Bowen and Ying, Zhitao and Pande, Vijay and Leskovec, Jure},
  booktitle={Advances in neural information processing systems},
  pages={6410--6421},
  year={2018}
}

@article{weininger1988smiles,
  title={SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules},
  author={Weininger, David},
  journal={Journal of chemical information and computer sciences},
  volume={28},
  number={1},
  pages={31--36},
  year={1988},
  publisher={ACS Publications}
}

@inproceedings{dai2018syntax,
  title={Syntax-Directed Variational Autoencoder for Structured Data},
  author={Dai, Hanjun and Tian, Yingtao and Dai, Bo and Skiena, Steven and Song, Le},
  booktitle={International Conference on Learning Representations},
  year={2018}
}

@article{podda2020deep,
  title={A deep generative model for fragment-based molecule generation},
  author={Podda, Marco and Bacciu, Davide and Micheli, Alessio},
  journal={arXiv preprint arXiv:2002.12826},
  year={2020}
}
@inproceedings{simonovsky2018graphvae,
  title={Graphvae: Towards generation of small graphs using variational autoencoders},
  author={Simonovsky, Martin and Komodakis, Nikos},
  booktitle={International Conference on Artificial Neural Networks},
  pages={412--422},
  year={2018},
  organization={Springer}
}

@inproceedings{liu2018constrained,
  title={Constrained graph variational autoencoders for molecule design},
  author={Liu, Qi and Allamanis, Miltiadis and Brockschmidt, Marc and Gaunt, Alexander},
  booktitle={Advances in neural information processing systems},
  pages={7795--7804},
  year={2018}
}

@inproceedings{kusner2017grammar,
  title={Grammar Variational Autoencoder},
  author={Kusner, Matt J and Paige, Brooks and Hern{\'a}ndez-Lobato, Jos{\'e} Miguel},
  booktitle={International Conference on Machine Learning},
  pages={1945--1954},
  year={2017}
}

@article{gomez2018automatic,
  title={Automatic chemical design using a data-driven continuous representation of molecules},
  author={G{\'o}mez-Bombarelli, Rafael and Wei, Jennifer N and Duvenaud, David and Hern{\'a}ndez-Lobato, Jos{\'e} Miguel and S{\'a}nchez-Lengeling, Benjam{\'\i}n and Sheberla, Dennis and Aguilera-Iparraguirre, Jorge and Hirzel, Timothy D and Adams, Ryan P and Aspuru-Guzik, Al{\'a}n},
  journal={ACS central science},
  volume={4},
  number={2},
  pages={268--276},
  year={2018},
  publisher={ACS Publications}
}

@article{irwin2012zinc,
  title={ZINC: a free tool to discover chemistry for biology},
  author={Irwin, John J and Sterling, Teague and Mysinger, Michael M and Bolstad, Erin S and Coleman, Ryan G},
  journal={Journal of chemical information and modeling},
  volume={52},
  number={7},
  pages={1757--1768},
  year={2012},
  publisher={ACS Publications}
}

@article{madhawa2019graphnvp,
  title={Graphnvp: An invertible flow model for generating molecular graphs},
  author={Madhawa, Kaushalya and Ishiguro, Katushiko and Nakago, Kosuke and Abe, Motoki},
  journal={arXiv preprint arXiv:1905.11600},
  year={2019}
}

%% EBM
@inproceedings{tieleman2008training,
	title={Training restricted Boltzmann machines using approximations to the likelihood gradient},
	author={Tieleman, Tijmen},
	booktitle={Proceedings of the 25th international conference on Machine learning},
	pages={1064--1071},
	year={2008}
}


%% latent space mcmc
@inproceedings{bengio2013better,
	title={Better mixing via deep representations},
	author={Bengio, Yoshua and Mesnil, Gr{\'e}goire and Dauphin, Yann and Rifai, Salah},
	booktitle={International conference on machine learning},
	pages={552--560},
	year={2013}
}



@article{brock2018large,
	title={Large scale gan training for high fidelity natural image synthesis},
	author={Brock, Andrew and Donahue, Jeff and Simonyan, Karen},
	journal={arXiv preprint arXiv:1809.11096},
	year={2018}
}

@article{hochreiter1997long,
  title={Long short-term memory},
  author={Hochreiter, Sepp and Schmidhuber, J{\"u}rgen},
  journal={Neural computation},
  volume={9},
  number={8},
  pages={1735--1780},
  year={1997},
  publisher={MIT Press}
}

@inproceedings{ghosh2020from,
title={From Variational to Deterministic Autoencoders},
author={Partha Ghosh and Mehdi S. M. Sajjadi and Antonio Vergari and Michael Black and Bernhard Scholkopf},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://openreview.net/forum?id=S1g7tpEYDS}
}

@inproceedings{sutton2000policy,
  title={Policy gradient methods for reinforcement learning with function approximation},
  author={Sutton, Richard S and McAllester, David A and Singh, Satinder P and Mansour, Yishay},
  booktitle={Advances in neural information processing systems},
  pages={1057--1063},
  year={2000}
}

@inproceedings{paszke2019pytorch,
  title={PyTorch: An imperative style, high-performance deep learning library},
  author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  booktitle={Advances in Neural Information Processing Systems},
  pages={8024--8035},
  year={2019}
}

@inproceedings{samanta2019nevae,
  title={NeVAE: A Deep Generative Model for Molecular Graphs},
  author={Samanta, Bidisha and Abir, DE and Jana, Gourhari and Chattaraj, Pratim Kumar and Ganguly, Niloy and Rodriguez, Manuel Gomez},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={33},
  pages={1110--1117},
  year={2019}
}

@article{shi2020graphaf,
  title={GraphAF: a flow-based autoregressive model for molecular graph generation},
  author={Shi, Chence and Xu, Minkai and Zhu, Zhaocheng and Zhang, Weinan and Zhang, Ming and Tang, Jian},
  journal={arXiv preprint arXiv:2001.09382},
  year={2020}
}

%% data
@article{cifar10,
	title= {CIFAR-10 (Canadian Institute for Advanced Research)},
	journal= {},
	author= {Alex Krizhevsky and Vinod Nair and Geoffrey Hinton},
	year= {},
	url= {http://www.cs.toronto.edu/~kriz/cifar.html},
	keywords= {Dataset},
	terms= {}
}

@article{netzer2011reading,
  title={Reading digits in natural images with unsupervised feature learning},
  author={Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},
  year={2011}
}

@inproceedings{kim2018semi,
  title={Semi-Amortized Variational Autoencoders},
  author={Kim, Yoon and Wiseman, Sam and Miller, Andrew and Sontag, David and Rush, Alexander},
  booktitle={International Conference on Machine Learning},
  pages={2678--2687},
  year={2018}
}

@article{cifka2018eval,
  title={Eval all, trust a few, do wrong to none: Comparing sentence generation models},
  author={C{\'\i}fka, Ond{\v{r}}ej and Severyn, Aliaksei and Alfonseca, Enrique and Filippova, Katja},
  journal={arXiv preprint arXiv:1804.07972},
  year={2018}
}

@inproceedings{li-etal-2019-surprisingly,
    title = "A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text",
    author = "Li, Bohan  and
      He, Junxian  and
      Neubig, Graham  and
      Berg-Kirkpatrick, Taylor  and
      Yang, Yiming",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-1370",
    doi = "10.18653/v1/D19-1370",
    pages = "3603--3614",
    abstract = "When trained effectively, the Variational Autoencoder (VAE) is both a powerful language model and an effective representation learning framework. In practice, however, VAEs are trained with the evidence lower bound (ELBO) as a surrogate objective to the intractable marginal data likelihood. This approach to training yields unstable results, frequently leading to a disastrous local optimum known as posterior collapse. In this paper, we investigate a simple fix for posterior collapse which yields surprisingly effective results. The combination of two known heuristics, previously considered only in isolation, substantially improves held-out likelihood, reconstruction, and latent representation learning when compared with previous state-of-the-art methods. More interestingly, while our experiments demonstrate superiority on these principle evaluations, our method obtains a worse ELBO. We use these results to argue that the typical surrogate objective for VAEs may not be sufficient or necessarily appropriate for balancing the goals of representation learning and data distribution modeling.",
}

@misc{asuncion2007uci,
  title={UCI machine learning repository},
  author={Asuncion, Arthur and Newman, David},
  year={2007}
}

@inproceedings{bowman-etal-2015-large,
    title = "A large annotated corpus for learning natural language inference",
    author = "Bowman, Samuel R.  and
      Angeli, Gabor  and
      Potts, Christopher  and
      Manning, Christopher D.",
    booktitle = "Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing",
    month = sep,
    year = "2015",
    address = "Lisbon, Portugal",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D15-1075",
    doi = "10.18653/v1/D15-1075",
    pages = "632--642",
}

@inproceedings{yang2017dilated,
  author    = {Zichao Yang and
               Zhiting Hu and
               Ruslan Salakhutdinov and
               Taylor Berg{-}Kirkpatrick},
  title     = {Improved Variational Autoencoders for Text Modeling using Dilated
               Convolutions},
  booktitle = {Proceedings of the 34th International Conference on Machine Learning,
               {ICML} 2017, Sydney, NSW, Australia, 6-11 August 2017},
  pages     = {3881--3890},
  year      = {2017},
  url       = {http://proceedings.mlr.press/v70/yang17d.html},
  timestamp = {Wed, 29 May 2019 08:41:45 +0200},
  biburl    = {https://dblp.org/rec/bib/conf/icml/YangHSB17},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{marcus1993building,
 author = {Marcus, Mitchell P. and Marcinkiewicz, Mary Ann and Santorini, Beatrice},
 title = {Building a Large Annotated Corpus of English: The Penn Treebank},
 journal = {Comput. Linguist.},
 issue_date = {June 1993},
 volume = {19},
 number = {2},
 month = jun,
 year = {1993},
 issn = {0891-2017},
 pages = {313--330},
 numpages = {18},
 url = {http://dl.acm.org/citation.cfm?id=972470.972475},
 acmid = {972475},
 publisher = {MIT Press},
 address = {Cambridge, MA, USA},
} 


@Book{cover2012elements,
  author =       "Thomas M. Cover and Joy A. Thomas",
  title =        "Elements of information theory {(2.} ed.)",
  publisher =    "Wiley",
  year =         "2006",
  URL =          "http://www.elementsofinformationtheory.com/",
  ISBN =         "978-0-471-24195-9",
  timestamp =    "Wed, 10 Jul 2019 10:47:04 +0200",
  biburl =       "https://dblp.org/rec/bib/books/daglib/0016881",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@inproceedings{bowman-etal-2016-generating,
    title = "Generating Sentences from a Continuous Space",
    author = "Bowman, Samuel R.  and
      Vilnis, Luke  and
      Vinyals, Oriol  and
      Dai, Andrew  and
      Jozefowicz, Rafal  and
      Bengio, Samy",
    booktitle = "Proceedings of The 20th {SIGNLL} Conference on Computational Natural Language Learning",
    month = aug,
    year = "2016",
    address = "Berlin, Germany",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/K16-1002",
    doi = "10.18653/v1/K16-1002",
    pages = "10--21",
}

%% for anomaly
@inproceedings{ZongSMCLCC18,
  author    = {Bo Zong and
               Qi Song and
               Martin Renqiang Min and
               Wei Cheng and
               Cristian Lumezanu and
               Dae{-}ki Cho and
               Haifeng Chen},
  title     = {Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly
               Detection},
  booktitle = {6th International Conference on Learning Representations, {ICLR} 2018,
               Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings},
  publisher = {OpenReview.net},
  year      = {2018},
  url       = {https://openreview.net/forum?id=BJJLHbb0-},
  timestamp = {Thu, 25 Jul 2019 14:25:50 +0200},
  biburl    = {https://dblp.org/rec/conf/iclr/ZongSMCLCC18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{ZhaiCLZ16,
  author    = {Shuangfei Zhai and
               Yu Cheng and
               Weining Lu and
               Zhongfei Zhang},
  editor    = {Maria{-}Florina Balcan and
               Kilian Q. Weinberger},
  title     = {Deep Structured Energy Based Models for Anomaly Detection},
  booktitle = {Proceedings of the 33nd International Conference on Machine Learning,
               {ICML} 2016, New York City, NY, USA, June 19-24, 2016},
  series    = {{JMLR} Workshop and Conference Proceedings},
  volume    = {48},
  pages     = {1100--1109},
  publisher = {JMLR.org},
  year      = {2016},
  url       = {http://proceedings.mlr.press/v48/zhai16.html},
  timestamp = {Wed, 29 May 2019 08:41:46 +0200},
  biburl    = {https://dblp.org/rec/conf/icml/ZhaiCLZ16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{zenati2018efficient,
  title={Efficient gan-based anomaly detection},
  author={Zenati, Houssam and Foo, Chuan Sheng and Lecouat, Bruno and Manek, Gaurav and Chandrasekhar, Vijay Ramaseshan},
  journal={arXiv preprint arXiv:1802.06222},
  year={2018}
}


%% vampprior
@inproceedings{tomczak2018vae,
  title={VAE with a VampPrior},
  author={Tomczak, Jakub and Welling, Max},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={1214--1223},
  year={2018}
}

%% LARS
@inproceedings{bauer2019resampled,
  title={Resampled Priors for Variational Autoencoders},
  author={Bauer, Matthias and Mnih, Andriy},
  booktitle={The 22nd International Conference on Artificial Intelligence and Statistics},
  pages={66--75},
  year={2019}
}

%%ARAE
@inproceedings{zhao2018adversarially,
  title={Adversarially Regularized Autoencoders},
  author={Zhao, Junbo and Kim, Yoon and Zhang, Kelly and Rush, Alexander and LeCun, Yann},
  booktitle={International Conference on Machine Learning},
  pages={5902--5911},
  year={2018}
}

%%2VAE
@inproceedings{dai2018diagnosing,
  title={Diagnosing and Enhancing VAE Models},
  author={Dai, Bin and Wipf, David},
  booktitle={International Conference on Learning Representations},
  year={2019}
}

%% initialization
@inproceedings{glorot2010understanding,
  title={Understanding the difficulty of training deep feedforward neural networks},
  author={Glorot, Xavier and Bengio, Yoshua},
  booktitle={Proceedings of the thirteenth international conference on artificial intelligence and statistics},
  pages={249--256},
  year={2010}
}

%% GLO
@article{bojanowski2017optimizing,
  title={Optimizing the latent space of generative networks},
  author={Bojanowski, Piotr and Joulin, Armand and Lopez-Paz, David and Szlam, Arthur},
  journal={arXiv preprint arXiv:1707.05776},
  year={2017}
}

%% SRI
@article{nijkamp2019learning1,
  title={Learning Deep Generative Models with Short Run Inference Dynamics},
  author={Nijkamp, Erik and Pang, Bo and Han, Tian and Zhou, Alex and Zhu, Song-Chun and Wu, Ying Nian},
  journal={arXiv preprint arXiv:1912.01909},
  year={2019}
}

%% WVAE
@article{tolstikhin2017wasserstein,
  title={Wasserstein auto-encoders},
  author={Tolstikhin, Ilya and Bousquet, Olivier and Gelly, Sylvain and Schoelkopf, Bernhard},
  journal={arXiv preprint arXiv:1711.01558},
  year={2017}
}

%% AAE
@article{makhzani2015adversarial,
  title={Adversarial autoencoders},
  author={Makhzani, Alireza and Shlens, Jonathon and Jaitly, Navdeep and Goodfellow, Ian and Frey, Brendan},
  journal={arXiv preprint arXiv:1511.05644},
  year={2015}
}

@article{nijkamp2019anatomy,
  title={On the anatomy of mcmc-based maximum likelihood learning of energy-based models},
  author={Nijkamp, Erik and Hill, Mitch and Han, Tian and Zhu, Song-Chun and Wu, Ying Nian},
  journal={arXiv preprint arXiv:1903.12370},
  year={2019}
}

%% two stage VAE
@article{dai2019diagnosing,
  title={Diagnosing and enhancing vae models},
  author={Dai, Bin and Wipf, David},
  journal={arXiv preprint arXiv:1903.05789},
  year={2019}
}

%% MH-GAN
@inproceedings{TurnerHFSY19,
  author    = {Ryan D. Turner and
               Jane Hung and
               Eric Frank and
               Yunus Saatchi and
               Jason Yosinski},
  editor    = {Kamalika Chaudhuri and
               Ruslan Salakhutdinov},
  title     = {Metropolis-Hastings Generative Adversarial Networks},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning,
               {ICML} 2019, 9-15 June 2019, Long Beach, California, {USA}},
  series    = {Proceedings of Machine Learning Research},
  volume    = {97},
  pages     = {6345--6353},
  publisher = {{PMLR}},
  year      = {2019},
  url       = {http://proceedings.mlr.press/v97/turner19a.html},
  timestamp = {Tue, 11 Jun 2019 15:37:38 +0200},
  biburl    = {https://dblp.org/rec/conf/icml/TurnerHFSY19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

%% vamp-prior
@inproceedings{TomczakW18,
  author    = {Jakub M. Tomczak and
               Max Welling},
  editor    = {Amos J. Storkey and
               Fernando P{\'{e}}rez{-}Cruz},
  title     = {{VAE} with a VampPrior},
  booktitle = {International Conference on Artificial Intelligence and Statistics,
               {AISTATS} 2018, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands,
               Spain},
  series    = {Proceedings of Machine Learning Research},
  volume    = {84},
  pages     = {1214--1223},
  publisher = {{PMLR}},
  year      = {2018},
  url       = {http://proceedings.mlr.press/v84/tomczak18a.html},
  timestamp = {Wed, 03 Apr 2019 18:17:22 +0200},
  biburl    = {https://dblp.org/rec/conf/aistats/TomczakW18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
%celebA
@inproceedings{liu2015faceattributes,
	Author = {Ziwei Liu and Ping Luo and Xiaogang Wang and Xiaoou Tang},
	Booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
	Month = December,
	Title = {Deep Learning Face Attributes in the Wild},
	Year = {2015}}
% FID
@article{lucic2017gans,
  title={Are gans created equal? a large-scale study},
  author={Lucic, Mario and Kurach, Karol and Michalski, Marcin and Gelly, Sylvain and Bousquet, Olivier},
  journal={arXiv preprint arXiv:1711.10337},
  year={2017}
}



@inproceedings{levine2013guided,
  author    = {Sergey Levine and
               Vladlen Koltun},
  title     = {Guided Policy Search},
  booktitle = {Proceedings of the 30th International Conference on Machine Learning,
               {ICML} 2013, Atlanta, GA, USA, 16-21 June 2013},
  pages     = {1--9},
  year      = {2013},
  url       = {http://proceedings.mlr.press/v28/levine13.html},
  timestamp = {Wed, 29 May 2019 08:41:46 +0200},
  biburl    = {https://dblp.org/rec/bib/conf/icml/LevineK13},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{kingma2016iaf,
	author    = {Diederik P. Kingma and
	Tim Salimans and
	Max Welling},
	title     = {Improving Variational Inference with Inverse Autoregressive Flow},
	journal   = {CoRR},
	volume    = {abs/1606.04934},
	year      = {2016},
	url       = {http://arxiv.org/abs/1606.04934},
	archivePrefix = {arXiv},
	eprint    = {1606.04934},
	timestamp = {Mon, 13 Aug 2018 16:47:58 +0200},
	biburl    = {https://dblp.org/rec/bib/journals/corr/KingmaSW16},
	bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{hendrycks2016gelu,
  author    = {Dan Hendrycks and
               Kevin Gimpel},
  title     = {Bridging Nonlinearities and Stochastic Regularizers with Gaussian
               Error Linear Units},
  journal   = {CoRR},
  volume    = {abs/1606.08415},
  year      = {2016},
  url       = {http://arxiv.org/abs/1606.08415},
  archivePrefix = {arXiv},
  eprint    = {1606.08415},
  timestamp = {Mon, 13 Aug 2018 16:46:20 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/HendrycksG16},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{hinton1985boltzmann,
  author    = {David H. Ackley and
               Geoffrey E. Hinton and
               Terrence J. Sejnowski},
  title     = {A Learning Algorithm for Boltzmann Machines},
  journal   = {Cognitive Science},
  volume    = {9},
  number    = {1},
  pages     = {147--169},
  year      = {1985},
  url       = {https://doi.org/10.1207/s15516709cog0901\_7},
  doi       = {10.1207/s15516709cog0901\_7},
  timestamp = {Wed, 14 Nov 2018 10:26:54 +0100},
  biburl    = {https://dblp.org/rec/bib/journals/cogsci/AckleyHS85},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{hinton1995helmholtz,
  author    = {Peter Dayan and
               Geoffrey E. Hinton and
               Radford M. Neal and
               Richard S. Zemel},
  title     = {The Helmholtz machine},
  journal   = {Neural Computation},
  volume    = {7},
  number    = {5},
  pages     = {889--904},
  year      = {1995},
  url       = {https://doi.org/10.1162/neco.1995.7.5.889},
  doi       = {10.1162/neco.1995.7.5.889},
  timestamp = {Wed, 14 Nov 2018 10:31:02 +0100},
  biburl    = {https://dblp.org/rec/bib/journals/neco/DayanHNZ95},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{han2019triangle,
  author    = {Tian Han and
               Erik Nijkamp and
               Xiaolin Fang and
               Mitch Hill and
               Song{-}Chun Zhu and
               Ying Nian Wu},
  title     = {Divergence Triangle for Joint Training of Generator Model, Energy-Based
               Model, and Inferential Model},
  booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
  pages     = {8670--8679},
  year      = {2019},
  url       = {http://openaccess.thecvf.com/content\_CVPR\_2019/html/Han\_Divergence\_Triangle\_for\_Joint\_Training\_of\_Generator\_Model\_Energy-Based\_Model\_CVPR\_2019\_paper.html},
  timestamp = {Mon, 18 Nov 2019 19:15:46 +0100},
  biburl    = {https://dblp.org/rec/bib/conf/cvpr/HanNFHZW19},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{hinton2002cd,
  author    = {Geoffrey E. Hinton},
  title     = {Training Products of Experts by Minimizing Contrastive Divergence},
  journal   = {Neural Computation},
  volume    = {14},
  number    = {8},
  pages     = {1771--1800},
  year      = {2002},
  url       = {https://doi.org/10.1162/089976602760128018},
  doi       = {10.1162/089976602760128018},
  timestamp = {Wed, 14 Nov 2018 10:31:08 +0100},
  biburl    = {https://dblp.org/rec/bib/journals/neco/Hinton02},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@InProceedings{sonderby2016ladder,
  author =       "Casper Kaae S{\o}nderby and Tapani Raiko and Lars
                 Maal{\o}e and S{\o}ren Kaae S{\o}nderby and Ole
                 Winther",
  title =        "Ladder Variational Autoencoders",
  booktitle =    "Advances in Neural Information Processing Systems 29:
                 Annual Conference on Neural Information Processing
                 Systems 2016, December 5-10, 2016, Barcelona, Spain",
  pages =        "3738--3746",
  year =         "2016",
  URL =          "http://papers.nips.cc/paper/6275-ladder-variational-autoencoders",
  timestamp =    "Fri, 03 Mar 2017 14:59:41 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/SonderbyRMSW16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{gregor2015draw,
  author =       "Karol Gregor and Ivo Danihelka and Alex Graves and
                 Danilo Jimenez Rezende and Daan Wierstra",
  title =        "{DRAW:} {A} Recurrent Neural Network For Image
                 Generation",
  booktitle =    "Proceedings of the 32nd International Conference on
                 Machine Learning, {ICML} 2015, Lille, France, 6-11 July
                 2015",
  pages =        "1462--1471",
  year =         "2015",
  URL =          "http://proceedings.mlr.press/v37/gregor15.html",
  timestamp =    "Wed, 29 May 2019 08:41:45 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/GregorDGRW15",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{kumar2019maximum,
  author =       "Rithesh Kumar and Anirudh Goyal and Aaron C. Courville
                 and Yoshua Bengio",
  title =        "Maximum Entropy Generators for Energy-Based Models",
  journal =      "CoRR",
  volume =       "abs/1901.08508",
  year =         "2019",
  URL =          "http://arxiv.org/abs/1901.08508",
  archiveprefix = "arXiv",
  eprint =       "1901.08508",
  timestamp =    "Sat, 02 Feb 2019 16:56:00 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/corr/abs-1901-08508",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{zhao2016energy,
  author =       "Junbo Jake Zhao and Micha{\"{e}}l Mathieu and Yann
                 LeCun",
  title =        "Energy-based Generative Adversarial Networks",
  booktitle =    "5th International Conference on Learning
                 Representations, {ICLR} 2017, Toulon, France, April
                 24-26, 2017, Conference Track Proceedings",
  year =         "2017",
  URL =          "https://openreview.net/forum?id=ryh9pmcee",
  timestamp =    "Thu, 25 Jul 2019 14:25:52 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/ZhaoML17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{kim2016deep,
  author =       "Taesup Kim and Yoshua Bengio",
  title =        "Deep Directed Generative Models with Energy-Based
                 Probability Estimation",
  journal =      "CoRR",
  volume =       "abs/1606.03439",
  year =         "2016",
  URL =          "http://arxiv.org/abs/1606.03439",
  archiveprefix = "arXiv",
  eprint =       "1606.03439",
  timestamp =    "Mon, 13 Aug 2018 16:48:27 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/KimB16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{rezende2015variational,
  author =       "Danilo Jimenez Rezende and Shakir Mohamed",
  title =        "Variational Inference with Normalizing Flows",
  booktitle =    "Proceedings of the 32nd International Conference on
                 Machine Learning, {ICML} 2015, Lille, France, 6-11 July
                 2015",
  pages =        "1530--1538",
  year =         "2015",
  URL =          "http://proceedings.mlr.press/v37/rezende15.html",
  timestamp =    "Wed, 29 May 2019 08:41:45 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/RezendeM15",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{krizhevsky2012imagenet,
  author =       "Alex Krizhevsky and Ilya Sutskever and Geoffrey E.
                 Hinton",
  title =        "ImageNet Classification with Deep Convolutional Neural
                 Networks",
  booktitle =    "Advances in Neural Information Processing Systems 25:
                 26th Annual Conference on Neural Information Processing
                 Systems 2012. Proceedings of a meeting held December
                 3-6, 2012, Lake Tahoe, Nevada, United States",
  pages =        "1106--1114",
  year =         "2012",
  URL =          "http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks",
  timestamp =    "Thu, 11 Dec 2014 17:34:07 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/KrizhevskySH12",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{goodfellow2014generative,
  author =       "Ian J. Goodfellow and Jean Pouget{-}Abadie and Mehdi
                 Mirza and Bing Xu and David Warde{-}Farley and Sherjil
                 Ozair and Aaron C. Courville and Yoshua Bengio",
  title =        "Generative Adversarial Nets",
  booktitle =    "Advances in Neural Information Processing Systems 27:
                 Annual Conference on Neural Information Processing
                 Systems 2014, December 8-13 2014, Montreal, Quebec,
                 Canada",
  pages =        "2672--2680",
  year =         "2014",
  URL =          "http://papers.nips.cc/paper/5423-generative-adversarial-nets",
  timestamp =    "Wed, 10 Dec 2014 21:34:12 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/GoodfellowPMXWOCB14",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{dinh2016density,
  author =       "Laurent Dinh and Jascha Sohl{-}Dickstein and Samy
                 Bengio",
  title =        "Density estimation using Real {NVP}",
  booktitle =    "5th International Conference on Learning
                 Representations, {ICLR} 2017, Toulon, France, April
                 24-26, 2017, Conference Track Proceedings",
  year =         "2017",
  URL =          "https://openreview.net/forum?id=HkpbnH9lx",
  timestamp =    "Thu, 25 Jul 2019 14:25:58 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/DinhSB17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{dinh2014nice,
  author =       "Laurent Dinh and David Krueger and Yoshua Bengio",
  title =        "{NICE:} Non-linear Independent Components Estimation",
  booktitle =    "3rd International Conference on Learning
                 Representations, {ICLR} 2015, San Diego, CA, USA, May
                 7-9, 2015, Workshop Track Proceedings",
  year =         "2015",
  URL =          "http://arxiv.org/abs/1410.8516",
  timestamp =    "Wed, 17 Jul 2019 10:40:54 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/DinhKB14",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{oord2016pixel,
  author =       "A{\"{a}}ron van den Oord and Nal Kalchbrenner and
                 Koray Kavukcuoglu",
  title =        "Pixel Recurrent Neural Networks",
  booktitle =    "Proceedings of the 33nd International Conference on
                 Machine Learning, {ICML} 2016, New York City, NY, USA,
                 June 19-24, 2016",
  pages =        "1747--1756",
  year =         "2016",
  URL =          "http://proceedings.mlr.press/v48/oord16.html",
  timestamp =    "Wed, 29 May 2019 08:41:46 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/OordKK16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{van2016conditional,
  author =       "A{\"{a}}ron van den Oord and Nal Kalchbrenner and
                 Lasse Espeholt and Koray Kavukcuoglu and Oriol Vinyals
                 and Alex Graves",
  title =        "Conditional Image Generation with Pixel{CNN}
                 Decoders",
  booktitle =    "Advances in Neural Information Processing Systems 29:
                 Annual Conference on Neural Information Processing
                 Systems 2016, December 5-10, 2016, Barcelona, Spain",
  pages =        "4790--4798",
  year =         "2016",
  URL =          "http://papers.nips.cc/paper/6527-conditional-image-generation-with-pixelcnn-decoders",
  timestamp =    "Fri, 03 Mar 2017 14:59:41 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/OordKEKVG16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{gutmann2010noise,
  author =       "Michael Gutmann and Aapo Hyv{\"{a}}rinen",
  title =        "Noise-contrastive estimation: {A} new estimation
                 principle for unnormalized statistical models",
  booktitle =    "Proceedings of the Thirteenth International Conference
                 on Artificial Intelligence and Statistics, {AISTATS}
                 2010, Chia Laguna Resort, Sardinia, Italy, May 13-15,
                 2010",
  pages =        "297--304",
  year =         "2010",
  URL =          "http://proceedings.mlr.press/v9/gutmann10a.html",
  timestamp =    "Wed, 29 May 2019 08:41:47 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/jmlr/GutmannH10",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{dai2014generative,
  author =       "Jifeng Dai and Yang Lu and Ying Nian Wu",
  title =        "Generative Modeling of Convolutional Neural Networks",
  booktitle =    "3rd International Conference on Learning
                 Representations, {ICLR} 2015, San Diego, CA, USA, May
                 7-9, 2015, Conference Track Proceedings",
  year =         "2015",
  URL =          "http://arxiv.org/abs/1412.6296",
  timestamp =    "Thu, 25 Jul 2019 14:25:37 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/DaiW14",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{xie2016theory,
  author =       "Jianwen Xie and Yang Lu and Song{-}Chun Zhu and Ying
                 Nian Wu",
  title =        "A Theory of Generative ConvNet",
  booktitle =    "Proceedings of the 33nd International Conference on
                 Machine Learning, {ICML} 2016, New York City, NY, USA,
                 June 19-24, 2016",
  pages =        "2635--2644",
  year =         "2016",
  URL =          "http://proceedings.mlr.press/v48/xiec16.html",
  timestamp =    "Wed, 29 May 2019 08:41:46 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/XieLZW16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{gao2018learning,
  author =       "Ruiqi Gao and Yang Lu and Junpei Zhou and Song{-}Chun
                 Zhu and Ying Nian Wu",
  title =        "Learning Generative ConvNets via Multi-Grid Modeling
                 and Sampling",
  booktitle =    "2018 {IEEE} Conference on Computer Vision and Pattern
                 Recognition, {CVPR} 2018, Salt Lake City, UT, USA, June
                 18-22, 2018",
  pages =        "9155--9164",
  year =         "2018",
  URL =          "http://openaccess.thecvf.com/content\_cvpr\_2018/html/Gao\_Learning\_Generative\_ConvNets\_CVPR\_2018\_paper.html",
  doi =          "10.1109/CVPR.2018.00954",
  timestamp =    "Wed, 16 Oct 2019 14:14:50 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/cvpr/GaoLZZW18",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{ngiam2011learning,
  author =       "Jiquan Ngiam and Zhenghao Chen and Pang Wei Koh and
                 Andrew Y. Ng",
  title =        "Learning Deep Energy Models",
  booktitle =    "Proceedings of the 28th International Conference on
                 Machine Learning, {ICML} 2011, Bellevue, Washington,
                 USA, June 28 - July 2, 2011",
  pages =        "1105--1112",
  year =         "2011",
  URL =          "https://icml.cc/2011/papers/557\_icmlpaper.pdf",
  timestamp =    "Wed, 03 Apr 2019 17:43:36 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/NgiamCKN11",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{jin2017introspective,
  author =       "Long Jin and Justin Lazarow and Zhuowen Tu",
  title =        "Introspective Classification with Convolutional Nets",
  booktitle =    "Advances in Neural Information Processing Systems 30:
                 Annual Conference on Neural Information Processing
                 Systems 2017, 4-9 December 2017, Long Beach, CA,
                 {USA}",
  pages =        "823--833",
  year =         "2017",
  URL =          "http://papers.nips.cc/paper/6684-introspective-classification-with-convolutional-nets",
  timestamp =    "Mon, 27 Nov 2017 12:38:48 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/JinLT17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{lazarow2017introspective,
  author =       "Justin Lazarow and Long Jin and Zhuowen Tu",
  title =        "Introspective Neural Networks for Generative
                 Modeling",
  booktitle =    "{IEEE} International Conference on Computer Vision,
                 {ICCV} 2017, Venice, Italy, October 22-29, 2017",
  pages =        "2793--2802",
  year =         "2017",
  URL =          "https://doi.org/10.1109/ICCV.2017.302",
  doi =          "10.1109/ICCV.2017.302",
  timestamp =    "Wed, 16 Oct 2019 14:14:51 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iccv/LazarowJT17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{heusel2017gans,
  author =       "Martin Heusel and Hubert Ramsauer and Thomas
                 Unterthiner and Bernhard Nessler and Sepp Hochreiter",
  title =        "{GAN}s Trained by a Two Time-Scale Update Rule
                 Converge to a Local Nash Equilibrium",
  booktitle =    "Advances in Neural Information Processing Systems 30:
                 Annual Conference on Neural Information Processing
                 Systems 2017, 4-9 December 2017, Long Beach, CA,
                 {USA}",
  pages =        "6626--6637",
  year =         "2017",
  URL =          "http://papers.nips.cc/paper/7240-gans-trained-by-a-two-time-scale-update-rule-converge-to-a-local-nash-equilibrium",
  timestamp =    "Tue, 23 Jul 2019 12:44:35 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/nips/HeuselRUNH17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{tu2007learning,
  author =       "Zhuowen Tu",
  title =        "Learning Generative Models via Discriminative
                 Approaches",
  booktitle =    "2007 {IEEE} Computer Society Conference on Computer
                 Vision and Pattern Recognition {(CVPR} 2007), 18-23
                 June 2007, Minneapolis, Minnesota, {USA}",
  year =         "2007",
  URL =          "https://doi.org/10.1109/CVPR.2007.383035",
  doi =          "10.1109/CVPR.2007.383035",
  timestamp =    "Wed, 16 Oct 2019 14:14:50 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/cvpr/Tu07",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{grathwohl2018ffjord,
  author =       "Will Grathwohl and Ricky T. Q. Chen and Jesse
                 Bettencourt and Ilya Sutskever and David Duvenaud",
  title =        "{FFJORD:} Free-Form Continuous Dynamics for Scalable
                 Reversible Generative Models",
  booktitle =    "7th International Conference on Learning
                 Representations, {ICLR} 2019, New Orleans, LA, USA, May
                 6-9, 2019",
  year =         "2019",
  URL =          "https://openreview.net/forum?id=rJxgknCcK7",
  timestamp =    "Thu, 25 Jul 2019 13:03:15 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/GrathwohlCBSD19",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{mnih2012fast,
  author =       "Andriy Mnih and Yee Whye Teh",
  title =        "A fast and simple algorithm for training neural
                 probabilistic language models",
  booktitle =    "Proceedings of the 29th International Conference on
                 Machine Learning, {ICML} 2012, Edinburgh, Scotland, UK,
                 June 26 - July 1, 2012",
  year =         "2012",
  URL =          "http://icml.cc/2012/papers/855.pdf",
  timestamp =    "Wed, 03 Apr 2019 17:43:37 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/MnihT12",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{kingma2014efficient,
  author =       "Diederik P. Kingma and Max Welling",
  title =        "Efficient Gradient-Based Inference through
                 Transformations between Bayes Nets and Neural Nets",
  booktitle =    "Proceedings of the 31th International Conference on
                 Machine Learning, {ICML} 2014, Beijing, China, 21-26
                 June 2014",
  pages =        "1782--1790",
  year =         "2014",
  URL =          "http://proceedings.mlr.press/v32/kingma14.html",
  timestamp =    "Wed, 29 May 2019 08:41:45 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/KingmaW14",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{salimans2017pixelcnn++,
  author =       "Tim Salimans and Andrej Karpathy and Xi Chen and
                 Diederik P. Kingma",
  title =        "Pixel{CNN}++: Improving the Pixel{CNN} with
                 Discretized Logistic Mixture Likelihood and Other
                 Modifications",
  booktitle =    "5th International Conference on Learning
                 Representations, {ICLR} 2017, Toulon, France, April
                 24-26, 2017, Conference Track Proceedings",
  year =         "2017",
  URL =          "https://openreview.net/forum?id=BJrFC6ceg",
  timestamp =    "Thu, 25 Jul 2019 14:25:50 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/SalimansK0K17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{fox2012tutorial,
  author =       "Charles W. Fox and Stephen J. Roberts",
  title =        "A tutorial on variational Bayesian inference",
  journal =      "Artif. Intell. Rev.",
  volume =       "38",
  number =       "2",
  pages =        "85--95",
  year =         "2012",
  URL =          "https://doi.org/10.1007/s10462-011-9236-8",
  doi =          "10.1007/s10462-011-9236-8",
  timestamp =    "Wed, 14 Nov 2018 10:30:37 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/air/FoxR12",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{finn2016connection,
  author =       "Chelsea Finn and Paul F. Christiano and Pieter Abbeel
                 and Sergey Levine",
  title =        "A Connection between Generative Adversarial Networks,
                 Inverse Reinforcement Learning, and Energy-Based
                 Models",
  journal =      "CoRR",
  volume =       "abs/1611.03852",
  year =         "2016",
  URL =          "http://arxiv.org/abs/1611.03852",
  archiveprefix = "arXiv",
  eprint =       "1611.03852",
  timestamp =    "Mon, 13 Aug 2018 16:47:13 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/FinnCAL16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{tran2019discrete,
  author =       "Dustin Tran and Keyon Vafa and Kumar Krishna Agrawal
                 and Laurent Dinh and Ben Poole",
  title =        "Discrete Flows: Invertible Generative Models of
                 Discrete Data",
  booktitle =    "Deep Generative Models for Highly Structured Data,
                 {ICLR} 2019 Workshop, New Orleans, Louisiana, United
                 States, May 6, 2019",
  year =         "2019",
  URL =          "https://openreview.net/forum?id=rJlo4UIt\_E",
  timestamp =    "Thu, 25 Jul 2019 16:26:32 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/TranVADP19",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{kumar2019videoflow,
  author =       "Manoj Kumar and Mohammad Babaeizadeh and Dumitru Erhan
                 and Chelsea Finn and Sergey Levine and Laurent Dinh and
                 Durk Kingma",
  title =        "VideoFlow: {A} Flow-Based Generative Model for Video",
  journal =      "CoRR",
  volume =       "abs/1903.01434",
  year =         "2019",
  URL =          "http://arxiv.org/abs/1903.01434",
  archiveprefix = "arXiv",
  eprint =       "1903.01434",
  timestamp =    "Sat, 30 Mar 2019 19:27:21 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/corr/abs-1903-01434",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{khemakhem2019variational,
  author =       "Ilyes Khemakhem and Diederik P. Kingma and Aapo
                 Hyv{\"{a}}rinen",
  title =        "Variational Autoencoders and Nonlinear {ICA:} {A}
                 Unifying Framework",
  journal =      "CoRR",
  volume =       "abs/1907.04809",
  year =         "2019",
  URL =          "http://arxiv.org/abs/1907.04809",
  archiveprefix = "arXiv",
  eprint =       "1907.04809",
  timestamp =    "Wed, 17 Jul 2019 10:27:36 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/abs-1907-04809",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{hinton2006fast,
  author =       "Geoffrey E. Hinton and Simon Osindero and Yee Whye
                 Teh",
  title =        "A Fast Learning Algorithm for Deep Belief Nets",
  journal =      "Neural Computation",
  volume =       "18",
  number =       "7",
  pages =        "1527--1554",
  year =         "2006",
  URL =          "https://doi.org/10.1162/neco.2006.18.7.1527",
  doi =          "10.1162/neco.2006.18.7.1527",
  timestamp =    "Wed, 14 Nov 2018 10:31:04 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/neco/HintonOT06",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{salakhutdinov2010efficient,
  author =       "Ruslan Salakhutdinov and Hugo Larochelle",
  title =        "Efficient Learning of Deep Boltzmann Machines",
  booktitle =    "Proceedings of the Thirteenth International Conference
                 on Artificial Intelligence and Statistics, {AISTATS}
                 2010, Chia Laguna Resort, Sardinia, Italy, May 13-15,
                 2010",
  pages =        "693--700",
  year =         "2010",
  URL =          "http://proceedings.mlr.press/v9/salakhutdinov10a.html",
  timestamp =    "Wed, 29 May 2019 08:41:47 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/jmlr/SalakhutdinovL10",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Book{amit1989world,
  author =       "Daniel J. Amit",
  title =        "Modeling brain function: the world of attractor neural
                 networks, 1st Edition",
  publisher =    "Cambridge Univ. Press",
  year =         "1989",
  URL =          "http://www.worldcat.org/oclc/19922497",
  ISBN =         "0-521-42124-1",
  timestamp =    "Wed, 26 Apr 2017 17:48:52 +0200",
  biburl =       "https://dblp.org/rec/bib/books/lib/Amit89",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{szegedy2016rethinking,
  author =       "Christian Szegedy and Vincent Vanhoucke and Sergey
                 Ioffe and Jonathon Shlens and Zbigniew Wojna",
  title =        "Rethinking the Inception Architecture for Computer
                 Vision",
  booktitle =    "2016 {IEEE} Conference on Computer Vision and Pattern
                 Recognition, {CVPR} 2016, Las Vegas, NV, USA, June
                 27-30, 2016",
  pages =        "2818--2826",
  year =         "2016",
  URL =          "https://doi.org/10.1109/CVPR.2016.308",
  doi =          "10.1109/CVPR.2016.308",
  timestamp =    "Wed, 16 Oct 2019 14:14:50 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/cvpr/SzegedyVISW16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{kingma2015adam,
  author =       "Diederik P. Kingma and Jimmy Ba",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/journals/corr/KingmaB14",
  booktitle =    "3rd International Conference on Learning
                 Representations, {ICLR} 2015, San Diego, CA, USA, May
                 7-9, 2015, Conference Track Proceedings",
  timestamp =    "Thu, 25 Jul 2019 14:25:37 +0200",
  title =        "Adam: {A} Method for Stochastic Optimization",
  URL =          "http://arxiv.org/abs/1412.6980",
  year =         "2015",
  bdsk-url-1 =   "http://arxiv.org/abs/1412.6980",
}

@Article{kingma2013inference,
  archiveprefix = "arXiv",
  author =       "Diederik P. Kingma",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/journals/corr/Kingma13",
  eprint =       "1306.0733",
  journal =      "CoRR",
  timestamp =    "Mon, 13 Aug 2018 16:47:02 +0200",
  title =        "Fast Gradient-Based Inference with Continuous Latent
                 Variable Models in Auxiliary Form",
  URL =          "http://arxiv.org/abs/1306.0733",
  volume =       "abs/1306.0733",
  year =         "2013",
  bdsk-url-1 =   "http://arxiv.org/abs/1306.0733",
}

@InProceedings{kingma2013auto,
  author =       "Diederik P. Kingma and Max Welling",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/journals/corr/KingmaW13",
  booktitle =    "2nd International Conference on Learning
                 Representations, {ICLR} 2014, Banff, AB, Canada, April
                 14-16, 2014, Conference Track Proceedings",
  timestamp =    "Thu, 04 Apr 2019 13:20:07 +0200",
  title =        "Auto-Encoding Variational Bayes",
  URL =          "http://arxiv.org/abs/1312.6114",
  year =         "2014",
  bdsk-url-1 =   "http://arxiv.org/abs/1312.6114",
}

@InProceedings{kingma2018glow,
  author =       "Diederik P. Kingma and Prafulla Dhariwal",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/nips/KingmaD18",
  booktitle =    "Advances in Neural Information Processing Systems 31:
                 Annual Conference on Neural Information Processing
                 Systems 2018, NeurIPS 2018, 3-8 December 2018,
                 Montr{\'{e}}al, Canada.",
  pages =        "10236--10245",
  timestamp =    "Sun, 16 Dec 2018 17:30:05 +0100",
  title =        "Glow: Generative Flow with Invertible 1x1
                 Convolutions",
  URL =          "http://papers.nips.cc/paper/8224-glow-generative-flow-with-invertible-1x1-convolutions",
  year =         "2018",
  bdsk-url-1 =   "http://papers.nips.cc/paper/8224-glow-generative-flow-with-invertible-1x1-convolutions",
}

@InProceedings{dinh2017realnvp,
  author =       "Laurent Dinh and Jascha Sohl{-}Dickstein and Samy
                 Bengio",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/DinhSB17",
  booktitle =    "5th International Conference on Learning
                 Representations, {ICLR} 2017, Toulon, France, April
                 24-26, 2017, Conference Track Proceedings",
  timestamp =    "Thu, 25 Jul 2019 14:25:58 +0200",
  title =        "Density estimation using Real {NVP}",
  URL =          "https://openreview.net/forum?id=HkpbnH9lx",
  year =         "2017",
  bdsk-url-1 =   "https://openreview.net/forum?id=HkpbnH9lx",
}

@InProceedings{salimans2015bridge,
  author =       "Tim Salimans and Diederik P. Kingma and Max Welling",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/icml/SalimansKW15",
  booktitle =    "Proceedings of the 32nd International Conference on
                 Machine Learning, {ICML} 2015, Lille, France, 6-11 July
                 2015",
  pages =        "1218--1226",
  timestamp =    "Wed, 29 May 2019 08:41:46 +0200",
  title =        "Markov Chain Monte Carlo and Variational Inference:
                 Bridging the Gap",
  URL =          "http://proceedings.mlr.press/v37/salimans15.html",
  year =         "2015",
  bdsk-url-1 =   "http://proceedings.mlr.press/v37/salimans15.html",
}

@InProceedings{han2017abp,
  author =       "Tian Han and Yang Lu and Song{-}Chun Zhu and Ying Nian
                 Wu",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/aaai/HanLZW17",
  booktitle =    "Proceedings of the Thirty-First {AAAI} Conference on
                 Artificial Intelligence, February 4-9, 2017, San
                 Francisco, California, {USA.}",
  pages =        "1976--1984",
  timestamp =    "Tue, 21 May 2019 09:04:47 +0200",
  title =        "Alternating Back-Propagation for Generator Network",
  URL =          "http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14784",
  year =         "2017",
  bdsk-url-1 =   "http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14784",
}

@Article{xie2019dynamic,
  archiveprefix = "arXiv",
  author =       "Jianwen Xie and Song{-}Chun Zhu and Ying Nian Wu",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/journals/corr/abs-1909-11975",
  eprint =       "1909.11975",
  journal =      "IEEE Transactions on Pattern Analysis and Machine
                 Intelligence (TPAMI)",
  timestamp =    "Fri, 27 Sep 2019 13:04:21 +0200",
  title =        "Learning Energy-based Spatial-Temporal Generative
                 ConvNets for Dynamic Patterns",
  URL =          "http://arxiv.org/abs/1909.11975",
  volume =       "abs/1909.11975",
  year =         "2019",
  bdsk-url-1 =   "http://arxiv.org/abs/1909.11975",
}

@InProceedings{xie2019abptt,
  author =       "Jianwen Xie and Ruiqi Gao and Zilong Zheng and
                 Song{-}Chun Zhu and Ying Nian Wu",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/aaai/XieGZZW19",
  booktitle =    "The Thirty-Third {AAAI} Conference on Artificial
                 Intelligence, {AAAI} 2019, The Thirty-First Innovative
                 Applications of Artificial Intelligence Conference,
                 {IAAI} 2019, The Ninth {AAAI} Symposium on Educational
                 Advances in Artificial Intelligence, {EAAI} 2019,
                 Honolulu, Hawaii, USA, January 27 - February 1, 2019.",
  doi =          "10.1609/aaai.v33i01.33015498",
  pages =        "5498--5507",
  timestamp =    "Wed, 25 Sep 2019 11:05:09 +0200",
  title =        "Learning Dynamic Generator Model by Alternating
                 Back-Propagation through Time",
  URL =          "https://doi.org/10.1609/aaai.v33i01.33015498",
  year =         "2019",
  bdsk-url-1 =   "https://doi.org/10.1609/aaai.v33i01.33015498",
  bdsk-url-2 =   "http://dx.doi.org/10.1609/aaai.v33i01.33015498",
}

@InProceedings{xie2018coop,
  author =       "Jianwen Xie and Yang Lu and Ruiqi Gao and Ying Nian
                 Wu",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/aaai/XieLGW18",
  booktitle =    "Proceedings of the Thirty-Second {AAAI} Conference on
                 Artificial Intelligence, (AAAI-18), the 30th innovative
                 Applications of Artificial Intelligence (IAAI-18), and
                 the 8th {AAAI} Symposium on Educational Advances in
                 Artificial Intelligence (EAAI-18), New Orleans,
                 Louisiana, USA, February 2-7, 2018",
  pages =        "4292--4301",
  timestamp =    "Wed, 22 May 2019 08:12:23 +0200",
  title =        "Cooperative Learning of Energy-Based Model and Latent
                 Variable Model via {MCMC} Teaching",
  URL =          "https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17432",
  year =         "2018",
  bdsk-url-1 =   "https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17432",
}

@InProceedings{goyal2017walkback,
  author =       "Anirudh Goyal and Nan Rosemary Ke and Surya Ganguli
                 and Yoshua Bengio",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/nips/GoyalKGB17",
  booktitle =    "Advances in Neural Information Processing Systems 30:
                 Annual Conference on Neural Information Processing
                 Systems 2017, 4-9 December 2017, Long Beach, CA,
                 {USA}",
  pages =        "4392--4402",
  timestamp =    "Tue, 23 Jul 2019 12:44:35 +0200",
  title =        "Variational Walkback: Learning a Transition Operator
                 as a Stochastic Recurrent Net",
  URL =          "http://papers.nips.cc/paper/7026-variational-walkback-learning-a-transition-operator-as-a-stochastic-recurrent-net",
  year =         "2017",
  bdsk-url-1 =   "http://papers.nips.cc/paper/7026-variational-walkback-learning-a-transition-operator-as-a-stochastic-recurrent-net",
}

@InProceedings{behrmann2019invertible,
  author =       "Jens Behrmann and Will Grathwohl and Ricky T. Q. Chen
                 and David Duvenaud and J{\"{o}}rn{-}Henrik Jacobsen",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
  biburl =       "https://dblp.org/rec/bib/conf/icml/BehrmannGCDJ19",
  booktitle =    "Proceedings of the 36th International Conference on
                 Machine Learning, {ICML} 2019, 9-15 June 2019, Long
                 Beach, California, {USA}",
  pages =        "573--582",
  timestamp =    "Tue, 11 Jun 2019 15:37:38 +0200",
  title =        "Invertible Residual Networks",
  URL =          "http://proceedings.mlr.press/v97/behrmann19a.html",
  year =         "2019",
  bdsk-url-1 =   "http://proceedings.mlr.press/v97/behrmann19a.html",
}

@InProceedings{xie2016cooperative,
  author =       "Jianwen Xie and Yang Lu and Ruiqi Gao and Ying Nian
                 Wu",
  title =        "Cooperative Learning of Energy-Based Model and Latent
                 Variable Model via {MCMC} Teaching",
  booktitle =    "Proceedings of the Thirty-Second {AAAI} Conference on
                 Artificial Intelligence, (AAAI-18), the 30th innovative
                 Applications of Artificial Intelligence (IAAI-18), and
                 the 8th {AAAI} Symposium on Educational Advances in
                 Artificial Intelligence (EAAI-18), New Orleans,
                 Louisiana, USA, February 2-7, 2018",
  pages =        "4292--4301",
  year =         "2018",
  URL =          "https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17432",
  timestamp =    "Wed, 22 May 2019 08:12:23 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/aaai/XieLGW18",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Book{murphy2012machine,
  author =       "Kevin P. Murphy",
  title =        "Machine learning - a probabilistic perspective",
  series =       "Adaptive computation and machine learning series",
  publisher =    "{MIT} Press",
  year =         "2012",
  ISBN =         "0-262-01802-0",
  timestamp =    "Wed, 26 Apr 2017 17:48:08 +0200",
  biburl =       "https://dblp.org/rec/bib/books/lib/Murphy12",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{radford2015unsupervised,
  author =       "Alec Radford and Luke Metz and Soumith Chintala",
  title =        "Unsupervised Representation Learning with Deep
                 Convolutional Generative Adversarial Networks",
  booktitle =    "4th International Conference on Learning
                 Representations, {ICLR} 2016, San Juan, Puerto Rico,
                 May 2-4, 2016, Conference Track Proceedings",
  year =         "2016",
  URL =          "http://arxiv.org/abs/1511.06434",
  timestamp =    "Thu, 25 Jul 2019 14:25:38 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/RadfordMC15",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{zemel2001localist,
  author =       "Richard S. Zemel and Michael Mozer",
  title =        "Localist Attractor Networks",
  journal =      "Neural Computation",
  volume =       "13",
  number =       "5",
  pages =        "1045--1064",
  year =         "2001",
  URL =          "https://doi.org/10.1162/08997660151134325",
  doi =          "10.1162/08997660151134325",
  timestamp =    "Wed, 14 Nov 2018 10:31:21 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/neco/ZemelM01",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{krotov2019unsupervised,
  author =       "Dmitry Krotov and John J. Hopfield",
  title =        "Unsupervised learning by competing hidden units",
  journal =      "Proc. Natl. Acad. Sci. {U.S.A.}",
  volume =       "116",
  number =       "16",
  pages =        "7723--7731",
  year =         "2019",
  URL =          "https://doi.org/10.1073/pnas.1820458116",
  doi =          "10.1073/pnas.1820458116",
  timestamp =    "Mon, 29 Jul 2019 15:59:08 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/pnas/KrotovH19",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{cheng2017underdamped,
  author =       "Xiang Cheng and Niladri S. Chatterji and Peter L.
                 Bartlett and Michael I. Jordan",
  title =        "Underdamped Langevin {MCMC:} {A} non-asymptotic
                 analysis",
  booktitle =    "Conference On Learning Theory, {COLT} 2018, Stockholm,
                 Sweden, 6-9 July 2018",
  pages =        "300--323",
  year =         "2018",
  URL =          "http://proceedings.mlr.press/v75/cheng18a.html",
  timestamp =    "Wed, 03 Apr 2019 18:17:23 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/colt/ChengCBJ18",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{cheng2018sharp,
  author =       "Xiang Cheng and Niladri S. Chatterji and Yasin
                 Abbasi{-}Yadkori and Peter L. Bartlett and Michael I.
                 Jordan",
  title =        "Sharp Convergence Rates for Langevin Dynamics in the
                 Nonconvex Setting",
  journal =      "CoRR",
  volume =       "abs/1805.01648",
  year =         "2018",
  URL =          "http://arxiv.org/abs/1805.01648",
  archiveprefix = "arXiv",
  eprint =       "1805.01648",
  timestamp =    "Mon, 13 Aug 2018 16:46:12 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/abs-1805-01648",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{li2017mmd,
  author =       "Chun{-}Liang Li and Wei{-}Cheng Chang and Yu Cheng and
                 Yiming Yang and Barnab{\'{a}}s P{\'{o}}czos",
  title =        "{MMD} {GAN:} Towards Deeper Understanding of Moment
                 Matching Network",
  booktitle =    "Advances in Neural Information Processing Systems 30:
                 Annual Conference on Neural Information Processing
                 Systems 2017, 4-9 December 2017, Long Beach, CA,
                 {USA}",
  pages =        "2203--2213",
  year =         "2017",
  URL =          "http://papers.nips.cc/paper/6815-mmd-gan-towards-deeper-understanding-of-moment-matching-network",
  timestamp =    "Tue, 23 Jul 2019 12:44:35 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/nips/LiCCYP17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{miyato2018spectral,
  author =       "Takeru Miyato and Toshiki Kataoka and Masanori Koyama
                 and Yuichi Yoshida",
  title =        "Spectral Normalization for Generative Adversarial
                 Networks",
  booktitle =    "6th International Conference on Learning
                 Representations, {ICLR} 2018, Vancouver, BC, Canada,
                 April 30 - May 3, 2018, Conference Track Proceedings",
  year =         "2018",
  URL =          "https://openreview.net/forum?id=B1QRgziT-",
  timestamp =    "Thu, 04 Apr 2019 13:20:10 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/MiyatoKKY18",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{gulrajani2017improved,
  author =       "Ishaan Gulrajani and Faruk Ahmed and Mart{\'{\i}}n
                 Arjovsky and Vincent Dumoulin and Aaron C. Courville",
  title =        "Improved Training of Wasserstein {GAN}s",
  booktitle =    "Advances in Neural Information Processing Systems 30:
                 Annual Conference on Neural Information Processing
                 Systems 2017, 4-9 December 2017, Long Beach, CA,
                 {USA}",
  pages =        "5767--5777",
  year =         "2017",
  URL =          "http://papers.nips.cc/paper/7159-improved-training-of-wasserstein-gans",
  timestamp =    "Tue, 23 Jul 2019 12:44:35 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/nips/GulrajaniAADC17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{welling2009herding,
  author =       "Max Welling",
  title =        "Herding dynamical weights to learn",
  booktitle =    "Proceedings of the 26th Annual International
                 Conference on Machine Learning, {ICML} 2009, Montreal,
                 Quebec, Canada, June 14-18, 2009",
  pages =        "1121--1128",
  year =         "2009",
  URL =          "https://doi.org/10.1145/1553374.1553517",
  doi =          "10.1145/1553374.1553517",
  timestamp =    "Tue, 06 Nov 2018 16:58:29 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/icml/Welling09",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{xie2018learning,
  author =       "Jianwen Xie and Zilong Zheng and Ruiqi Gao and Wenguan
                 Wang and Song{-}Chun Zhu and Ying Nian Wu",
  title =        "Learning Descriptor Networks for 3{D} Shape Synthesis
                 and Analysis",
  booktitle =    "2018 {IEEE} Conference on Computer Vision and Pattern
                 Recognition, {CVPR} 2018, Salt Lake City, UT, USA, June
                 18-22, 2018",
  pages =        "8629--8638",
  year =         "2018",
  URL =          "http://openaccess.thecvf.com/content\_cvpr\_2018/html/Xie\_Learning\_Descriptor\_Networks\_CVPR\_2018\_paper.html",
  doi =          "10.1109/CVPR.2018.00900",
  timestamp =    "Wed, 16 Oct 2019 14:14:50 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/cvpr/XieZGWZW18",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{xie2017synthesizing,
  author =       "Jianwen Xie and Song{-}Chun Zhu and Ying Nian Wu",
  title =        "Synthesizing Dynamic Patterns by Spatial-Temporal
                 Generative ConvNet",
  booktitle =    "2017 {IEEE} Conference on Computer Vision and Pattern
                 Recognition, {CVPR} 2017, Honolulu, HI, USA, July
                 21-26, 2017",
  pages =        "1061--1069",
  year =         "2017",
  URL =          "https://doi.org/10.1109/CVPR.2017.119",
  doi =          "10.1109/CVPR.2017.119",
  timestamp =    "Wed, 16 Oct 2019 14:14:50 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/cvpr/XieZW17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{dai2017calibrating,
  author =       "Zihang Dai and Amjad Almahairi and Philip Bachman and
                 Eduard H. Hovy and Aaron C. Courville",
  title =        "Calibrating Energy-based Generative Adversarial
                 Networks",
  booktitle =    "5th International Conference on Learning
                 Representations, {ICLR} 2017, Toulon, France, April
                 24-26, 2017, Conference Track Proceedings",
  year =         "2017",
  URL =          "https://openreview.net/forum?id=SyxeqhP9ll",
  timestamp =    "Thu, 25 Jul 2019 14:25:40 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/DaiABHC17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{zhu1998frame,
  author =       "Song Chun Zhu and Ying Nian Wu and David Mumford",
  title =        "Filters, Random Fields and Maximum Entropy {(FRAME):}
                 Towards a Unified Theory for Texture Modeling",
  journal =      "International Journal of Computer Vision",
  volume =       "27",
  number =       "2",
  pages =        "107--126",
  year =         "1998",
  URL =          "https://doi.org/10.1023/A:1007925832420",
  doi =          "10.1023/A:1007925832420",
  timestamp =    "Wed, 17 May 2017 14:25:23 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/ijcv/ZhuWM98",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{xie2016convnet,
  author =       "Jianwen Xie and Yang Lu and Song{-}Chun Zhu and Ying
                 Nian Wu",
  title =        "A Theory of Generative ConvNet",
  booktitle =    "Proceedings of the 33nd International Conference on
                 Machine Learning, {ICML} 2016, New York City, NY, USA,
                 June 19-24, 2016",
  pages =        "2635--2644",
  year =         "2016",
  URL =          "http://proceedings.mlr.press/v48/xiec16.html",
  timestamp =    "Wed, 29 May 2019 08:41:46 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/XieLZW16",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{lu2016deepframe,
  author =       "Yang Lu and Song{-}Chun Zhu and Ying Nian Wu",
  title =        "Learning {FRAME} Models Using {CNN} Filters",
  booktitle =    "Proceedings of the Thirtieth {AAAI} Conference on
                 Artificial Intelligence, February 12-17, 2016, Phoenix,
                 Arizona, {USA}",
  pages =        "1902--1910",
  year =         "2016",
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  timestamp =    "Tue, 21 May 2019 09:04:47 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/aaai/LuZW16",
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@Article{wu2000equivalence,
  author =       "Ying Nian Wu and Song Chun Zhu and Xiuwen Liu",
  title =        "Equivalence of Julesz Ensembles and {FRAME} Models",
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  biburl =       "https://dblp.org/rec/bib/journals/ijcv/WuZL00",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
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@Book{bishop,
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  publisher =    "Springer",
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  URL =          "http://www.worldcat.org/oclc/71008143",
  ISBN =         "978-0-387-31073-2",
  timestamp =    "Wed, 26 Apr 2017 17:48:52 +0200",
  biburl =       "https://dblp.org/rec/bib/books/lib/Bishop07",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{geman84gibbs,
  author =       "Stuart Geman and Donald Geman",
  title =        "Stochastic Relaxation, Gibbs Distributions, and the
                 Bayesian Restoration of Images",
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  URL =          "https://doi.org/10.1109/TPAMI.1984.4767596",
  doi =          "10.1109/TPAMI.1984.4767596",
  timestamp =    "Wed, 14 Nov 2018 10:51:11 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/pami/GemanG84",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{pcd,
  author =       "Tijmen Tieleman",
  title =        "Training restricted Boltzmann machines using
                 approximations to the likelihood gradient",
  booktitle =    "Machine Learning, Proceedings of the Twenty-Fifth
                 International Conference {(ICML} 2008), Helsinki,
                 Finland, June 5-9, 2008",
  pages =        "1064--1071",
  year =         "2008",
  URL =          "https://doi.org/10.1145/1390156.1390290",
  doi =          "10.1145/1390156.1390290",
  timestamp =    "Tue, 06 Nov 2018 16:58:28 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/icml/Tieleman08",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InCollection{rbm,
  author =       "Geoffrey E. Hinton",
  title =        "A Practical Guide to Training Restricted Boltzmann
                 Machines",
  booktitle =    "Neural Networks: Tricks of the Trade - Second
                 Edition",
  pages =        "599--619",
  year =         "2012",
  URL =          "https://doi.org/10.1007/978-3-642-35289-8\_32",
  doi =          "10.1007/978-3-642-35289-8\_32",
  timestamp =    "Wed, 25 Sep 2019 17:41:07 +0200",
  biburl =       "https://dblp.org/rec/bib/series/lncs/Hinton12",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Book{DBLP:series/lncs/7700,
  editor =       "Gr{\'{e}}goire Montavon and Genevieve B. Orr and
                 Klaus{-}Robert M{\"{u}}ller",
  title =        "Neural Networks: Tricks of the Trade - Second
                 Edition",
  series =       "Lecture Notes in Computer Science",
  volume =       "7700",
  publisher =    "Springer",
  year =         "2012",
  URL =          "https://doi.org/10.1007/978-3-642-35289-8",
  doi =          "10.1007/978-3-642-35289-8",
  ISBN =         "978-3-642-35288-1",
  timestamp =    "Wed, 25 Sep 2019 17:41:07 +0200",
  biburl =       "https://dblp.org/rec/bib/series/lncs/7700",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{frame,
  author =       "Song Chun Zhu and Ying Nian Wu and David Mumford",
  title =        "Filters, Random Fields and Maximum Entropy {(FRAME):}
                 Towards a Unified Theory for Texture Modeling",
  journal =      "International Journal of Computer Vision",
  volume =       "27",
  number =       "2",
  pages =        "107--126",
  year =         "1998",
  URL =          "https://doi.org/10.1023/A:1007925832420",
  doi =          "10.1023/A:1007925832420",
  timestamp =    "Wed, 17 May 2017 14:25:23 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/ijcv/ZhuWM98",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{cd_convergence,
  author =       "Alan L. Yuille",
  title =        "The Convergence of Contrastive Divergences",
  booktitle =    "Advances in Neural Information Processing Systems 17
                 [Neural Information Processing Systems, {NIPS} 2004,
                 December 13-18, 2004, Vancouver, British Columbia,
                 Canada]",
  pages =        "1593--1600",
  year =         "2004",
  URL =          "http://papers.nips.cc/paper/2617-the-convergence-of-contrastive-divergences",
  timestamp =    "Thu, 11 Dec 2014 17:34:08 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/Yuille04a",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{hinton2002poe,
  author =       "Geoffrey E. Hinton",
  title =        "Training Products of Experts by Minimizing Contrastive
                 Divergence",
  journal =      "Neural Computation",
  volume =       "14",
  number =       "8",
  pages =        "1771--1800",
  year =         "2002",
  URL =          "https://doi.org/10.1162/089976602760128018",
  doi =          "10.1162/089976602760128018",
  timestamp =    "Wed, 14 Nov 2018 10:31:08 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/neco/Hinton02",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{bengio2004learning,
  author =       "Yoshua Bengio and Olivier Delalleau and Nicolas Le
                 Roux and Jean{-}Fran{\c{c}}ois Paiement and Pascal
                 Vincent and Marie Ouimet",
  title =        "Learning Eigenfunctions Links Spectral Embedding and
                 Kernel {PCA}",
  journal =      "Neural Computation",
  volume =       "16",
  number =       "10",
  pages =        "2197--2219",
  year =         "2004",
  URL =          "https://doi.org/10.1162/0899766041732396",
  doi =          "10.1162/0899766041732396",
  timestamp =    "Wed, 14 Nov 2018 10:31:13 +0100",
  biburl =       "https://dblp.org/rec/bib/journals/neco/BengioDRPVO04",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{abbeel2004apprenticeship,
  author =       "Pieter Abbeel and Andrew Y. Ng",
  title =        "Apprenticeship learning via inverse reinforcement
                 learning",
  booktitle =    "Machine Learning, Proceedings of the Twenty-first
                 International Conference {(ICML} 2004), Banff, Alberta,
                 Canada, July 4-8, 2004",
  year =         "2004",
  URL =          "https://doi.org/10.1145/1015330.1015430",
  doi =          "10.1145/1015330.1015430",
  timestamp =    "Tue, 06 Nov 2018 16:58:29 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/icml/PieterN04",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{seung1998learning,
  author =       "H. Sebastian Seung",
  title =        "Learning Continuous Attractors in Recurrent Networks",
  booktitle =    "Advances in Neural Information Processing Systems 10,
                 {[NIPS} Conference, Denver, Colorado, USA, 1997]",
  pages =        "654--660",
  year =         "1997",
  URL =          "http://papers.nips.cc/paper/1369-learning-continuous-attractors-in-recurrent-networks",
  timestamp =    "Thu, 11 Dec 2014 17:34:08 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/Seung97",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{Wang03modelingtextured,
  author =       "Yizhou Wang and Song Chun Zhu",
  title =        "Modeling Textured Motion : Particle, Wave and Sketch",
  booktitle =    "9th {IEEE} International Conference on Computer Vision
                 {(ICCV} 2003), 14-17 October 2003, Nice, France",
  pages =        "213--220",
  year =         "2003",
  URL =          "https://doi.org/10.1109/ICCV.2003.1238343",
  doi =          "10.1109/ICCV.2003.1238343",
  timestamp =    "Wed, 16 Oct 2019 14:14:51 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iccv/WangZ03",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
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@InProceedings{MnihGregor2014,
  author =       "Andriy Mnih and Karol Gregor",
  title =        "Neural Variational Inference and Learning in Belief
                 Networks",
  booktitle =    "Proceedings of the 31th International Conference on
                 Machine Learning, {ICML} 2014, Beijing, China, 21-26
                 June 2014",
  pages =        "1791--1799",
  year =         "2014",
  URL =          "http://proceedings.mlr.press/v32/mnih14.html",
  timestamp =    "Wed, 29 May 2019 08:41:46 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/icml/MnihG14",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
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@InProceedings{matconvnn,
  author =       "Andrea Vedaldi and Karel Lenc",
  title =        "MatConvNet: Convolutional Neural Networks for
                 {MATLAB}",
  booktitle =    "Proceedings of the 23rd Annual {ACM} Conference on
                 Multimedia Conference, {MM} '15, Brisbane, Australia,
                 October 26 - 30, 2015",
  pages =        "689--692",
  year =         "2015",
  URL =          "https://doi.org/10.1145/2733373.2807412",
  doi =          "10.1145/2733373.2807412",
  timestamp =    "Tue, 06 Nov 2018 16:58:36 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/mm/VedaldiL15",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
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@InProceedings{kulkarni2015inverse,
  author =       "Tejas D. Kulkarni and William F. Whitney and Pushmeet
                 Kohli and Joshua B. Tenenbaum",
  title =        "Deep Convolutional Inverse Graphics Network",
  booktitle =    "Advances in Neural Information Processing Systems 28:
                 Annual Conference on Neural Information Processing
                 Systems 2015, December 7-12, 2015, Montreal, Quebec,
                 Canada",
  pages =        "2539--2547",
  year =         "2015",
  URL =          "http://papers.nips.cc/paper/5851-deep-convolutional-inverse-graphics-network",
  timestamp =    "Fri, 08 Apr 2016 19:32:52 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/nips/KulkarniWKT15",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{montufar2014number,
  author =       "Guido F. Mont{\'{u}}far and Razvan Pascanu and
                 KyungHyun Cho and Yoshua Bengio",
  title =        "On the Number of Linear Regions of Deep Neural
                 Networks",
  booktitle =    "Advances in Neural Information Processing Systems 27:
                 Annual Conference on Neural Information Processing
                 Systems 2014, December 8-13 2014, Montreal, Quebec,
                 Canada",
  pages =        "2924--2932",
  year =         "2014",
  URL =          "http://papers.nips.cc/paper/5422-on-the-number-of-linear-regions-of-deep-neural-networks",
  timestamp =    "Wed, 10 Dec 2014 21:34:12 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/nips/MontufarPCB14",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{alexey2015chair,
  author =       "Alexey Dosovitskiy and Jost Tobias Springenberg and
                 Thomas Brox",
  title =        "Learning to generate chairs with convolutional neural
                 networks",
  booktitle =    "{IEEE} Conference on Computer Vision and Pattern
                 Recognition, {CVPR} 2015, Boston, MA, USA, June 7-12,
                 2015",
  pages =        "1538--1546",
  year =         "2015",
  URL =          "https://doi.org/10.1109/CVPR.2015.7298761",
  doi =          "10.1109/CVPR.2015.7298761",
  timestamp =    "Wed, 16 Oct 2019 14:14:50 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/cvpr/DosovitskiySB15",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{liu2008monte,
  author =       "Tim Hesterberg",
  title =        "Monte Carlo Strategies in Scientific Computing",
  journal =      "Technometrics",
  volume =       "44",
  number =       "4",
  pages =        "403--404",
  year =         "2002",
  URL =          "https://doi.org/10.1198/tech.2002.s85",
  doi =          "10.1198/tech.2002.s85",
  timestamp =    "Sat, 27 May 2017 14:25:18 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/technometrics/Hesterberg02",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
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@InProceedings{ziebart2008maximum,
  author =       "Brian D. Ziebart and Andrew L. Maas and J. Andrew
                 Bagnell and Anind K. Dey",
  title =        "Maximum Entropy Inverse Reinforcement Learning",
  booktitle =    "Proceedings of the Twenty-Third {AAAI} Conference on
                 Artificial Intelligence, {AAAI} 2008, Chicago,
                 Illinois, USA, July 13-17, 2008",
  pages =        "1433--1438",
  year =         "2008",
  URL =          "http://www.aaai.org/Library/AAAI/2008/aaai08-227.php",
  timestamp =    "Mon, 10 Dec 2012 17:36:53 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/aaai/ZiebartMBD08",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{sonderby2016amortised,
  author =       "Casper Kaae S{\o}nderby and Jose Caballero and Lucas
                 Theis and Wenzhe Shi and Ferenc Husz{\'{a}}r",
  title =        "Amortised {MAP} Inference for Image Super-resolution",
  booktitle =    "5th International Conference on Learning
                 Representations, {ICLR} 2017, Toulon, France, April
                 24-26, 2017, Conference Track Proceedings",
  year =         "2017",
  URL =          "https://openreview.net/forum?id=S1RP6GLle",
  timestamp =    "Thu, 04 Apr 2019 13:20:09 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iclr/SonderbyCTSH17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
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@InProceedings{roth2017stabilizing,
  author =       "Kevin Roth and Aur{\'{e}}lien Lucchi and Sebastian
                 Nowozin and Thomas Hofmann",
  title =        "Stabilizing Training of Generative Adversarial
                 Networks through Regularization",
  booktitle =    "Advances in Neural Information Processing Systems 30:
                 Annual Conference on Neural Information Processing
                 Systems 2017, 4-9 December 2017, Long Beach, CA,
                 {USA}",
  pages =        "2018--2028",
  year =         "2017",
  URL =          "http://papers.nips.cc/paper/6797-stabilizing-training-of-generative-adversarial-networks-through-regularization",
  timestamp =    "Tue, 23 Jul 2019 12:44:35 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/nips/RothLNH17",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{della1995inducing,
  author =       "Stephen Della Pietra and Vincent J. Della Pietra and
                 John D. Lafferty",
  title =        "Inducing Features of Random Fields",
  journal =      "{IEEE} Trans. Pattern Anal. Mach. Intell.",
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  URL =          "https://doi.org/10.1109/34.588021",
  doi =          "10.1109/34.588021",
  timestamp =    "Wed, 17 May 2017 10:56:29 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/pami/PietraPL97",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}



@Article{barratt2018note,
  author =       "Shane T. Barratt and Rishi Sharma",
  title =        "A Note on the Inception Score",
  journal =      "CoRR",
  volume =       "abs/1801.01973",
  year =         "2018",
  URL =          "http://arxiv.org/abs/1801.01973",
  archiveprefix = "arXiv",
  eprint =       "1801.01973",
  timestamp =    "Mon, 09 Sep 2019 15:29:53 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/abs-1801-01973",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{zeiler2011adaptive,
  author =       "Matthew D. Zeiler and Graham W. Taylor and Rob
                 Fergus",
  title =        "Adaptive deconvolutional networks for mid and high
                 level feature learning",
  booktitle =    "{IEEE} International Conference on Computer Vision,
                 {ICCV} 2011, Barcelona, Spain, November 6-13, 2011",
  pages =        "2018--2025",
  year =         "2011",
  URL =          "https://doi.org/10.1109/ICCV.2011.6126474",
  doi =          "10.1109/ICCV.2011.6126474",
  timestamp =    "Wed, 16 Oct 2019 14:14:51 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/iccv/ZeilerTF11",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@Article{gatys2015style,
  author =       "Leon A. Gatys and Alexander S. Ecker and Matthias
                 Bethge",
  title =        "A Neural Algorithm of Artistic Style",
  journal =      "CoRR",
  volume =       "abs/1508.06576",
  year =         "2015",
  URL =          "http://arxiv.org/abs/1508.06576",
  archiveprefix = "arXiv",
  eprint =       "1508.06576",
  timestamp =    "Mon, 13 Aug 2018 16:48:03 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/corr/GatysEB15a",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{denton2015deep,
  author =       "Emily L. Denton and Soumith Chintala and Arthur Szlam
                 and Rob Fergus",
  title =        "Deep Generative Image Models using a Laplacian Pyramid
                 of Adversarial Networks",
  booktitle =    "Advances in Neural Information Processing Systems 28:
                 Annual Conference on Neural Information Processing
                 Systems 2015, December 7-12, 2015, Montreal, Quebec,
                 Canada",
  pages =        "1486--1494",
  year =         "2015",
  URL =          "http://papers.nips.cc/paper/5773-deep-generative-image-models-using-a-laplacian-pyramid-of-adversarial-networks",
  timestamp =    "Fri, 08 Apr 2016 19:32:52 +0200",
  biburl =       "https://dblp.org/rec/bib/conf/nips/DentonCSF15",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{salakhutdinov2009deep,
  author =       "Ruslan Salakhutdinov and Geoffrey E. Hinton",
  title =        "Deep Boltzmann Machines",
  booktitle =    "Proceedings of the Twelfth International Conference on
                 Artificial Intelligence and Statistics, {AISTATS} 2009,
                 Clearwater Beach, Florida, USA, April 16-18, 2009",
  pages =        "448--455",
  year =         "2009",
  URL =          "http://proceedings.mlr.press/v5/salakhutdinov09a.html",
  timestamp =    "Wed, 29 May 2019 08:41:48 +0200",
  biburl =       "https://dblp.org/rec/bib/journals/jmlr/SalakhutdinovH09",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
}

@InProceedings{lee2009convolutional,
  author =       "Honglak Lee and Roger B. Grosse and Rajesh Ranganath
                 and Andrew Y. Ng",
  title =        "Convolutional deep belief networks for scalable
                 unsupervised learning of hierarchical representations",
  booktitle =    "Proceedings of the 26th Annual International
                 Conference on Machine Learning, {ICML} 2009, Montreal,
                 Quebec, Canada, June 14-18, 2009",
  pages =        "609--616",
  year =         "2009",
  URL =          "https://doi.org/10.1145/1553374.1553453",
  doi =          "10.1145/1553374.1553453",
  timestamp =    "Wed, 14 Nov 2018 10:58:56 +0100",
  biburl =       "https://dblp.org/rec/bib/conf/icml/LeeGRN09",
  bibsource =    "dblp computer science bibliography, https://dblp.org",
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@InProceedings{ioffe2015batch,
  author =       "Sergey Ioffe and Christian Szegedy",
  title =        "Batch Normalization: Accelerating Deep Network
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@InProceedings{tu2018wasser,
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@InProceedings{arjovsky2017wasserstein,
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URL = { 
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},
eprint = { 
        https://doi.org/10.1021/acs.jcim.8b00839
    
}

}

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