@article{Rougier:2018,
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}

@article{Science:2018,
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@Misc{Roboto:2011,
  author =       {Christian Robertson},
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}

@Misc{SourceSerifPro:2014,
  author =       {Frank Grießhammer},
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  year =         2014,
  note =         {SIL Open Font License, version 1.1},
}

@Misc{SourceCodePro:2012,
  author =       {Paul D. Hunt},
  title =        {Source Code Pro (Adobe Systems)},
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  note =         {SIL Open Font License, version 1.1},
}

@article{Topalidou:2015,
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}

@article{Rougier:2017,
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  volume =       3,
  pages =        {e142},
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  github =       {https://github.com/ReScience/ReScience-article-2},
  keywords =     {journal},
  tags =         {OS},
}

@article{Sinha:2022,
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  code_doi = {},
  code_swh = {},
  data_url = {},
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  review_url = {},
  type = {Editorial},
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  keywords = {rescience c, machine learning, deep learning, python, pytorch}
}

@article{Sinha:2021,
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  code_swh = {},
  data_url = {},
  data_doi = {},
  review_url = {},
  type = {Editorial},
  language = {},
  domain = {},
  keywords = {machine learning, neurips, reproducibility challenge}
}

@article{Sinha:2020,
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  code_url = {},
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  code_swh = {},
  data_url = {},
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  review_url = {},
  type = {Editorial},
  language = {},
  domain = {},
  keywords = {machine learning, neurips, reproducibility challenge}
}

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}

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shekhovtsov2022vae,
title={{VAE} Approximation Error: {ELBO} and Exponential Families},
author={Alexander Shekhovtsov and Dmitrij Schlesinger and Boris Flach},
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year={2022},
url={https://openreview.net/forum?id=OIs3SxU5Ynl}
}

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  author = {Kingma, Diederik P and Welling, Max},
  
  keywords = {Machine Learning (stat.ML), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {Auto-Encoding Variational Bayes},
  
  publisher = {arXiv},
  
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@article{disarm,
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  url = {https://arxiv.org/abs/2006.10680},
  
  author = {Dong, Zhe and Mnih, Andriy and Tucker, George},
  
  keywords = {Machine Learning (cs.LG), Machine Learning (stat.ML), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {DisARM: An Antithetic Gradient Estimator for Binary Latent Variables},
  
  publisher = {arXiv},
  
  year = {2020},
  
  copyright = {arXiv.org perpetual, non-exclusive license}
}

@misc{arm,
  doi = {10.48550/ARXIV.1807.11143},
  
  url = {https://arxiv.org/abs/1807.11143},
  
  author = {Yin, Mingzhang and Zhou, Mingyuan},
  
  keywords = {Machine Learning (stat.ML), Machine Learning (cs.LG), Computation (stat.CO), Methodology (stat.ME), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks},
  
  publisher = {arXiv},
  
  year = {2018},
  
  copyright = {arXiv.org perpetual, non-exclusive license}
}


@misc{diagvae,
  doi = {10.48550/ARXIV.1903.05789},
  
  url = {https://arxiv.org/abs/1903.05789},
  
  author = {Dai, Bin and Wipf, David},
  
  keywords = {Machine Learning (cs.LG), Computer Vision and Pattern Recognition (cs.CV), Machine Learning (stat.ML), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {Diagnosing and Enhancing VAE Models},
  
  publisher = {arXiv},
  
  year = {2019},
  
  copyright = {arXiv.org perpetual, non-exclusive license}
}


@misc{cyclicalbeta,
  doi = {10.48550/ARXIV.1903.10145},
  
  url = {https://arxiv.org/abs/1903.10145},
  
  author = {Fu, Hao and Li, Chunyuan and Liu, Xiaodong and Gao, Jianfeng and Celikyilmaz, Asli and Carin, Lawrence},
  
  keywords = {Machine Learning (cs.LG), Artificial Intelligence (cs.AI), Computation and Language (cs.CL), Computer Vision and Pattern Recognition (cs.CV), Machine Learning (stat.ML), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing},
  
  publisher = {arXiv},
  
  year = {2019},
  
  copyright = {arXiv.org perpetual, non-exclusive license}
}

@inproceedings{Higgins2016betaVAELB,
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}

@misc{dcgan,
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  keywords = {Machine Learning (cs.LG), Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks},
  
  publisher = {arXiv},
  
  year = {2015},
  
  copyright = {arXiv.org perpetual, non-exclusive license}
}

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}

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@inproceedings{
  ddsp,
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}

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  year={2019}
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@misc{Inkawhich,
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}


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@inproceedings{ganfid,
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@misc{brock2019large,
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      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@inproceedings{
bae2023multirate,
title={Multi-Rate {VAE}: Train Once, Get the Full Rate-Distortion Curve},
author={Juhan Bae and Michael R. Zhang and Michael Ruan and Eric Wang and So Hasegawa and Jimmy Ba and Roger Baker Grosse},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=OJ8aSjCaMNK}
}