
%%%%%%%%%%%%%%%%%%%% CCA %%%%%%%%%%%%%%%%%%%%%%%%%%%
@article{pcca_bach,
  title={A probabilistic interpretation of canonical correlation analysis},
  author={Bach, Francis R and Jordan, Michael I},
  year={2005},
  publisher={Technical Report 688, Department of Statistics, University of California~…}
}

@article{pcca_klami,
  title={Probabilistic approach to detecting dependencies between data sets},
  author={Klami, Arto and Kaski, Samuel},
  journal={Neurocomputing},
  volume={72},
  number={1-3},
  pages={39--46},
  year={2008},
  publisher={Elsevier}
}

@article{dvcca,
  title={Deep variational canonical correlation analysis},
  author={Wang, Weiran and Yan, Xinchen and Lee, Honglak and Livescu, Karen},
  journal={arXiv preprint arXiv:1610.03454},
  year={2016}
}

@article{dpcca,
  title={Dynamic probabilistic CCA for analysis of affective behavior and fusion of continuous annotations},
  author={Nicolaou, Mihalis A and Pavlovic, Vladimir and Pantic, Maja},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={36},
  number={7},
  pages={1299--1311},
  year={2014},
  publisher={IEEE}
}

% article{d2pcca, title={Deep Dynamic Probabilistic Canonical Correlation Analysis},
%  author={Tang, Shiqin and Yu, Shujian and Dong, Yining and Qin, S. Joe},
%  journal={arXiv preprint arXiv:2502.05155},
%  year={2025}
%}

@INPROCEEDINGS{d2pcca,
  author={Tang, Shiqin and Yu, Shujian and Dong, Yining and Qin, S. Joe},
  booktitle={ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 
  title={Deep Dynamic Probabilistic Canonical Correlation Analysis}, 
  year={2025},
  volume={},
  number={},
  pages={1-5},
  keywords={Deep learning;Analytical models;Correlation;Buildings;Signal processing;Probabilistic logic;Encoding;Nonlinear dynamical systems;Speech processing;Convergence;Dynamical Probabilistic Canonical Correlation Analysis;Multiset;Deep Markov Model},
  doi={10.1109/ICASSP49660.2025.10887585}}

@inproceedings{my_dssm,
  title={A Hierarchical Taxonomy For Deep State Space Models},
  author={Tang, Shiqin and Feng, Pengxing and Yu, Shujian and Dong, Yining and Qin, S Joe},
  booktitle={ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={1--5},
  year={2025},
  organization={IEEE}
}

%%%%%%%%%%%%%%%%%%%% IB-Deterministic %%%%%%%%%%%%%%%%%%%%%%%%%%%

@article{ibvsdib,
  title={On the difference between the information bottleneck and the deep information bottleneck},
  author={Wieczorek, Aleksander and Roth, Volker},
  journal={Entropy},
  volume={22},
  number={2},
  pages={131},
  year={2020},
  publisher={MDPI}
}

@article{pfib09,
  title={Past-future information bottleneck in dynamical systems},
  author={Creutzig, Felix and Globerson, Amir and Tishby, Naftali},
  journal={Physical Review E—Statistical, Nonlinear, and Soft Matter Physics},
  volume={79},
  number={4},
  pages={041925},
  year={2009},
  publisher={APS}
}

@inproceedings{pfib15,
  title={Past-future Information Bottleneck for linear feedback systems},
  author={Amir, Nadav and Tiomkin, Stas and Tishby, Naftali},
  booktitle={2015 54th IEEE Conference on Decision and Control (CDC)},
  pages={5737--5742},
  year={2015},
  organization={IEEE}
}

@article{pfib24,
  title={Which bits went where? Past and future transfer entropy decomposition with the information bottleneck},
  author={Murphy, Kieran A and Yin, Zhuowen and Bassett, Dani S},
  journal={arXiv preprint arXiv:2411.04992},
  year={2024}
}

@article{nib1,
  title={Nonlinear information bottleneck},
  author={Kolchinsky, Artemy and Tracey, Brendan D and Wolpert, David H},
  journal={Entropy},
  volume={21},
  number={12},
  pages={1181},
  year={2019},
  publisher={MDPI}
}

@article{nib2,
  title={Estimating mixture entropy with pairwise distances},
  author={Kolchinsky, Artemy and Tracey, Brendan D},
  journal={Entropy},
  volume={19},
  number={7},
  pages={361},
  year={2017},
  publisher={MDPI}
}

@article{infoNCE,
  title={Representation learning with contrastive predictive coding},
  author={Oord, Aaron van den and Li, Yazhe and Vinyals, Oriol},
  journal={arXiv preprint arXiv:1807.03748},
  year={2018}
}

@inproceedings{cimCLR,
  title={A simple framework for contrastive learning of visual representations},
  author={Chen, Ting and Kornblith, Simon and Norouzi, Mohammad and Hinton, Geoffrey},
  booktitle={International conference on machine learning},
  pages={1597--1607},
  year={2020},
  organization={PMLR}
}


%%%%%%%%%%%%%%%%%%%% IB-VI %%%%%%%%%%%%%%%%%%%%%%%%%%%
@article{vib,
  title={Deep variational information bottleneck},
  author={Alemi, Alexander A and Fischer, Ian and Dillon, Joshua V and Murphy, Kevin},
  journal={arXiv preprint arXiv:1612.00410},
  year={2016}
}

@article{ceb,
  title={The conditional entropy bottleneck},
  author={Fischer, Ian},
  journal={Entropy},
  volume={22},
  number={9},
  pages={999},
  year={2020},
  publisher={MDPI}
}

@article{cpic22,
  title={Compressed predictive information coding},
  author={Meng, Rui and Luo, Tianyi and Bouchard, Kristofer},
  journal={arXiv preprint arXiv:2203.02051},
  year={2022}
}

@article{teb22,
  title={Transfer entropy bottleneck: Learning sequence to sequence information transfer},
  author={Kalajdzievski, Damjan and Mao, Ximeng and Fortier-Poisson, Pascal and Lajoie, Guillaume and Richards, Blake},
  journal={arXiv preprint arXiv:2211.16607},
  year={2022}
}

@article{tlib24,
  title={Latent representation and simulation of markov processes via time-lagged information bottleneck},
  author={Federici, Marco and Forr{\'e}, Patrick and Tomioka, Ryota and Veeling, Bastiaan S},
  journal={arXiv preprint arXiv:2309.07200},
  year={2023}
}

@article{spib21,
  title={State predictive information bottleneck},
  author={Wang, Dedi and Tiwary, Pratyush},
  journal={The Journal of Chemical Physics},
  volume={154},
  number={13},
  year={2021},
  publisher={AIP Publishing}
}

@article{mvib,
  title={Learning robust representations via multi-view information bottleneck},
  author={Federici, Marco and Dutta, Anjan and Forr{\'e}, Patrick and Kushman, Nate and Akata, Zeynep},
  journal={arXiv preprint arXiv:2002.07017},
  year={2020}
}

%%%%%%%%%%%%%%%%%%%% Other Methods %%%%%%%%%%%%%%%%%%%%%%%%%%%
@article{tck,
  title={Time series cluster kernel for learning similarities between multivariate time series with missing data},
  author={Mikalsen, Karl {\O}yvind and Bianchi, Filippo Maria and Soguero-Ruiz, Cristina and Jenssen, Robert},
  journal={Pattern Recognition},
  volume={76},
  pages={569--581},
  year={2018},
  publisher={Elsevier}
}

@article{avi, 
  title={Auto-encoding variational bayes},
  author={Kingma, Diederik P and Welling, Max},
  journal={arXiv preprint arXiv:1312.6114},
  year={2013}
}

@article{pyro,
  title={Pyro: Deep universal probabilistic programming},
  author={Bingham, Eli and Chen, Jonathan P and Jankowiak, Martin and Obermeyer, Fritz and Pradhan, Neeraj and Karaletsos, Theofanis and Singh, Rohit and Szerlip, Paul and Horsfall, Paul and Goodman, Noah D},
  journal={Journal of machine learning research},
  volume={20},
  number={28},
  pages={1--6},
  year={2019}
}

@inproceedings{resnet,
  title={Identity mappings in deep residual networks},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Computer Vision--ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11--14, 2016, Proceedings, Part IV 14},
  pages={630--645},
  year={2016},
  organization={Springer}
}

@inproceedings{dmm,
  title={Structured inference networks for nonlinear state space models},
  author={Krishnan, Rahul and Shalit, Uri and Sontag, David},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={31},
  number={1},
  year={2017}
}

@article{dvae,
  title={Dynamical variational autoencoders: A comprehensive review},
  author={Girin, Laurent and Leglaive, Simon and Bie, Xiaoyu and Diard, Julien and Hueber, Thomas and Alameda-Pineda, Xavier},
  journal={arXiv preprint arXiv:2008.12595},
  year={2020}
}

@inproceedings{cho2014gru,
  author    = {Kyunghyun Cho and Bart van Merriënboer and Caglar Gulcehre and Dzmitry Bahdanau and Fethi Bougares and Holger Schwenk and Yoshua Bengio},
  title     = {Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation},
  booktitle = {Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year      = {2014},
  pages     = {1724--1734},
  publisher = {Association for Computational Linguistics},
  doi       = {10.3115/v1/D14-1179}
}


@article{vrnn,
  title={A recurrent latent variable model for sequential data},
  author={Chung, Junyoung and Kastner, Kyle and Dinh, Laurent and Goel, Kratarth and Courville, Aaron C and Bengio, Yoshua},
  journal={Advances in neural information processing systems},
  volume={28},
  year={2015}
}

@article{ncca,
  title={Non-linear Canonical Correlation Analysis: A Compressed Representation Approach},
  author={Painsky, Amichai and Feder, Meir and Tishby, Naftali},
  journal={arXiv preprint arXiv:2502.05155},
  year={2025}
}

@article{gib,
author = {Chechik, Gal and Globerson, Amir and Tishby, Naftali and Weiss, Yair},
title = {Information Bottleneck for Gaussian Variables},
year = {2005},
issue_date = {12/1/2005},
publisher = {JMLR.org},
volume = {6},
issn = {1532-4435},
journal = {J. Mach. Learn. Res.},
month = dec,
pages = {165–188},
numpages = {24}
}

@article{ib,
  title={The information bottleneck method},
  author={Tishby, Naftali and Pereira, Fernando C and Bialek, William},
  journal={arXiv preprint physics/0004057},
  year={2000}
}

@inproceedings{cvae,
  title={Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech},
  author={Kim, Jaehyeon and Kong, Jungil and Son, Juhee},
  booktitle={International Conference on Machine Learning},
  pages={5530--5540},
  year={2021},
  organization={PMLR}
}

@misc{koller,
  title={Probabilistic Graphical Models: Principles and Techniques},
  author={Koller, Daphane},
  year={2009},
  publisher={The MIT Press}
}


%%%%%%%%%%%%%%%%%%%% Biology %%%%%%%%%%%%%%%%%%%%%%%%%%%
@article{fmri16,
  title={State-space model with deep learning for functional dynamics estimation in resting-state fMRI},
  author={Suk, Heung-Il and Wee, Chong-Yaw and Lee, Seong-Whan and Shen, Dinggang},
  journal={NeuroImage},
  volume={129},
  pages={292--307},
  year={2016},
  publisher={Elsevier}
}

@inproceedings{fmri19,
  title={Deep generative state-space modeling of FMRI images for psychiatric disorder diagnosis},
  author={Kusano, Koki and Tashiro, Tetsuo and Matsubara, Takashi and Uehara, Kuniaki},
  booktitle={2019 international joint conference on neural networks (IJCNN)},
  pages={1--7},
  year={2019},
  organization={IEEE}
}

@misc{eceo,
  author       = {Stefan, Z.},
  title        = {A toolbox for brain network construction and classification},
  year         = {2020},
  url          = {https://github.com/zzstefan/BrainNetClass},
  note         = {Accessed: 2025-02-11}
}

@misc{adni,
  author       = {Alzheimer's Disease Neuroimaging Initiative},
  title        = {The Alzheimer's Disease Neuroimaging Initiative},
  year         = {2025}, 
  url          = {https://adni.loni.usc.edu/},
  note         = {Accessed: 2025-02-11}
}

@article{abide,
  author    = {Di Martino, A. and Scheres, A. and Margulies, D. S. and et al.},
  title     = {The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism},
  journal   = {Molecular Psychiatry},
  year      = {2014},
  volume    = {19},
  number    = {6},
  pages     = {659--667},
  doi       = {10.1038/mp.2014.54},
  url       = {https://www.nature.com/articles/mp.2014.54}
}

@inproceedings{kpca,
  author    = {B. Schölkopf and A. Smola and K.-R. Müller},
  title     = {Kernel Principal Component Analysis},
  booktitle = {Proceedings of the 1997 Conference on Advances in Neural Information Processing Systems (NIPS 1997)},
  year      = {1997},
  pages     = {582--588},
  url       = {https://papers.nips.cc/paper/1997/hash/5b4d9034971fd4f13f315bdb2f8ad56d-Abstract.html}
}

@article{qin,
  title={Latent vector autoregressive modeling and feature analysis of high dimensional and noisy data from dynamic systems},
  author={Qin, S Joe},
  journal={AIChE Journal},
  volume={68},
  number={6},
  pages={e17703},
  year={2022},
  publisher={Wiley Online Library}
}

@article{lin,
  title={Quantifying common and distinct information in single-cell multimodal data with Tilted Canonical Correlation Analysis},
  author={Lin, Kevin Z and Zhang, Nancy R},
  journal={Proceedings of the National Academy of Sciences},
  volume={120},
  number={32},
  pages={e2303647120},
  year={2023},
  publisher={National Academy of Sciences}
}
