@article{mnih2015human,
  title={Human-level control through deep reinforcement learning},
  author={Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A and Veness, Joel and Bellemare, Marc G and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K and Ostrovski, Georg and others},
  journal={nature},
  volume={518},
  number={7540},
  pages={529--533},
  year={2015},
  publisher={Nature Publishing Group}
}

@inproceedings{lillicrap2015continuous,
  title={Continuous control with deep reinforcement learning},
  author={Lillicrap, Timothy P and Hunt, Jonathan J and Pritzel, Alexander and Heess, Nicolas and Erez, Tom and Tassa, Yuval and Silver, David and Wierstra, Daan},
  booktitle={4th International Conference on Learning Representations},
  year={2016}
}

@inproceedings{hessel2018rainbow,
  title={Rainbow: Combining improvements in deep reinforcement learning},
  author={Hessel, Matteo and Modayil, Joseph and Van Hasselt, Hado and Schaul, Tom and Ostrovski, Georg and Dabney, Will and Horgan, Dan and Piot, Bilal and Azar, Mohammad and Silver, David},
  booktitle={Thirty-second AAAI conference on artificial intelligence},
  year={2018}
}

@article{lake2017building,
  title={Building machines that learn and think like people},
  author={Lake, Brenden M and Ullman, Tomer D and Tenenbaum, Joshua B and Gershman, Samuel J},
  journal={Behavioral and brain sciences},
  volume={40},
  year={2017},
  publisher={Cambridge University Press}
}

@inproceedings{kaiser2019model,
  title={Model-based reinforcement learning for atari},
  author={Kaiser, Lukasz and Babaeizadeh, Mohammad and Milos, Piotr and Osinski, Blazej and Campbell, Roy H and Czechowski, Konrad and Erhan, Dumitru and Finn, Chelsea and Kozakowski, Piotr and Levine, Sergey and others},
  booktitle={8th International Conference on Learning Representations},
  year={2019}
}

@article{kalashnikov2018qt,
  title={Qt-opt: Scalable deep reinforcement learning for vision-based robotic manipulation},
  author={Kalashnikov, Dmitry and Irpan, Alex and Pastor, Peter and Ibarz, Julian and Herzog, Alexander and Jang, Eric and Quillen, Deirdre and Holly, Ethan and Kalakrishnan, Mrinal and Vanhoucke, Vincent and others},
  journal={arXiv preprint arXiv:1806.10293},
  year={2018}
}

@article{akkaya2019solving,
  title={Solving rubik's cube with a robot hand},
  author={Akkaya, Ilge and Andrychowicz, Marcin and Chociej, Maciek and Litwin, Mateusz and McGrew, Bob and Petron, Arthur and Paino, Alex and Plappert, Matthias and Powell, Glenn and Ribas, Raphael and others},
  journal={arXiv preprint arXiv:1910.07113},
  year={2019}
}

@article{lesort2018state,
  title={State representation learning for control: An overview},
  author={Lesort, Timoth{\'e}e and D{\'\i}az-Rodr{\'\i}guez, Natalia and Goudou, Jean-Franois and Filliat, David},
  journal={Neural Networks},
  volume={108},
  pages={379--392},
  year={2018},
  publisher={Elsevier}
}

@article{fischer2020conditional,
  title={The conditional entropy bottleneck},
  author={Fischer, Ian},
  journal={Entropy},
  volume={22},
  number={9},
  pages={999},
  year={2020},
  publisher={Multidisciplinary Digital Publishing Institute}
}

@article{tassa2018deepmind,
  title={Deepmind control suite},
  author={Tassa, Yuval and Doron, Yotam and Muldal, Alistair and Erez, Tom and Li, Yazhe and Casas, Diego de Las and Budden, David and Abdolmaleki, Abbas and Merel, Josh and Lefrancq, Andrew and others},
  journal={arXiv preprint arXiv:1801.00690},
  year={2018}
}

@inproceedings{lange2010deep,
  title={Deep auto-encoder neural networks in reinforcement learning},
  author={Lange, Sascha and Riedmiller, Martin},
  booktitle={The 2010 International Joint Conference on Neural Networks (IJCNN)},
  pages={1--8},
  year={2010},
  organization={IEEE}
}

@inproceedings{lange2012autonomous,
  title={Autonomous reinforcement learning on raw visual input data in a real world application},
  author={Lange, Sascha and Riedmiller, Martin and Voigtl{\"a}nder, Arne},
  booktitle={The 2012 international joint conference on neural networks (IJCNN)},
  pages={1--8},
  year={2012},
  organization={IEEE}
}

@article{wahlstrom2015pixels,
  title={From pixels to torques: Policy learning with deep dynamical models},
  author={Wahlstr{\"o}m, Niklas and Sch{\"o}n, Thomas B and Deisenroth, Marc Peter},
  journal={arXiv preprint arXiv:1502.02251},
  year={2015}
}

@inproceedings{watter2015embed,
  title={Embed to control: A locally linear latent dynamics model for control from raw images},
  author={Watter, Manuel and Springenberg, Jost Tobias and Boedecker, Joschka and Riedmiller, Martin},
  booktitle={Advances in Neural Information Processing Systems 28},
  pages={2746--2754},
  year={2015}
}

@inproceedings{hafner2019learning,
  title={Learning latent dynamics for planning from pixels},
  author={Hafner, Danijar and Lillicrap, Timothy and Fischer, Ian and Villegas, Ruben and Ha, David and Lee, Honglak and Davidson, James},
  booktitle={International Conference on Machine Learning},
  pages={2555--2565},
  year={2019},
  organization={PMLR}
}

@inproceedings{hafner2019dream,
  title={Dream to control: Learning behaviors by latent imagination},
  author={Hafner, Danijar and Lillicrap, Timothy and Ba, Jimmy and Norouzi, Mohammad},
  booktitle={8th International Conference on Learning Representations},
  year={2020}
}

@inproceedings{hafner2020mastering,
  title={Mastering atari with discrete world models},
  author={Hafner, Danijar and Lillicrap, Timothy and Norouzi, Mohammad and Ba, Jimmy},
  booktitle={9th International Conference on Learning Representations},
  year={2021}
}

@inproceedings{lee2019stochastic,
  title={Stochastic latent actor-critic: Deep reinforcement learning with a latent variable model},
  author={Lee, Alex X and Nagabandi, Anusha and Abbeel, Pieter and Levine, Sergey},
  booktitle={Advances in Neural Information Processing Systems 33},
  year={2020}
}

@article{zhang2018natural,
  title={Natural environment benchmarks for reinforcement learning},
  author={Zhang, Amy and Wu, Yuxin and Pineau, Joelle},
  journal={arXiv preprint arXiv:1811.06032},
  year={2018}
}

@inproceedings{caron2020unsupervised,
  title={Unsupervised learning of visual features by contrasting cluster assignments},
  author={Caron, Mathilde and Misra, Ishan and Mairal, Julien and Goyal, Priya and Bojanowski, Piotr and Joulin, Armand},
  booktitle={Advances in Neural Information Processing Systems 33},
  year={2020}
}

@inproceedings{xie2021propagate,
  title={Propagate yourself: Exploring pixel-level consistency for unsupervised visual representation learning},
  author={Xie, Zhenda and Lin, Yutong and Zhang, Zheng and Cao, Yue and Lin, Stephen and Hu, Han},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={16684--16693},
  year={2021}
}

@inproceedings{chen2020simple,
  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}
}

@inproceedings{henaff2020data,
  title={Data-efficient image recognition with contrastive predictive coding},
  author={Henaff, Olivier},
  booktitle={International Conference on Machine Learning},
  pages={4182--4192},
  year={2020},
  organization={PMLR}
}

@inproceedings{belghazi2018mutual,
  title={Mutual information neural estimation},
  author={Belghazi, Mohamed Ishmael and Baratin, Aristide and Rajeshwar, Sai and Ozair, Sherjil and Bengio, Yoshua and Courville, Aaron and Hjelm, Devon},
  booktitle={International Conference on Machine Learning},
  pages={531--540},
  year={2018},
  organization={PMLR}
}

@inproceedings{poole2019variational,
  title={On variational bounds of mutual information},
  author={Poole, Ben and Ozair, Sherjil and Van Den Oord, Aaron and Alemi, Alex and Tucker, George},
  booktitle={International Conference on Machine Learning},
  pages={5171--5180},
  year={2019},
  organization={PMLR}
}

@inproceedings{kim2018emi,
  title={Emi: Exploration with mutual information},
  author={Kim, Hyoungseok and Kim, Jaekyeom and Jeong, Yeonwoo and Levine, Sergey and Song, Hyun Oh},
  booktitle={Proceedings of the 36th International Conference on Machine Learning},
  pages={3360--3369},
  year={2019},
  organization={PMLR}
}

@inproceedings{srinivas2020curl,
  title={Curl: Contrastive unsupervised representations for reinforcement learning},
  author={Srinivas, Aravind and Laskin, Michael and Abbeel, Pieter},
  booktitle={Proceedings of the 37th International Conference on Machine Learning},
  pages={5639--5650},
  year={2020},
  organization={PMLR}
}

@inproceedings{mazoure2020deep,
  title={Deep reinforcement and infomax learning},
  author={Mazoure, Bogdan and Combes, Remi Tachet des and Doan, Thang and Bachman, Philip and Hjelm, R Devon},
  booktitle={Advances in Neural Information Processing Systems 33},
  year={2020}
}

@inproceedings{li2019multi,
  title={Multi-view reinforcement learning},
  author={Li, Minne and Wu, Lisheng and Ammar, Haitham Bou and Wang, Jun},
  booktitle={Advances in Neural Information Processing Systems 32},
  year={2019}
}

@inproceedings{chen2017double,
  title={Double-task deep q-learning with multiple views},
  author={Chen, Jun and Bai, Tingzhu and Huang, Xiangsheng and Guo, Xian and Yang, Jianing and Yao, Yuxing},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision Workshops},
  pages={1050--1058},
  year={2017}
}

@inproceedings{van2016deep,
  title={Deep reinforcement learning with double q-learning},
  author={Van Hasselt, Hado and Guez, Arthur and Silver, David},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  year={2016}
}

@inproceedings{wang2016dueling,
  title={Dueling network architectures for deep reinforcement learning},
  author={Wang, Ziyu and Schaul, Tom and Hessel, Matteo and Hasselt, Hado and Lanctot, Marc and Freitas, Nando},
  booktitle={International conference on machine learning},
  pages={1995--2003},
  year={2016},
  organization={PMLR}
}

@inproceedings{federici2020learning,
  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},
  booktitle={8th International Conference on Learning Representations},
  year={2020}
}

@inproceedings{wang2019deep,
  title={Deep multi-view information bottleneck},
  author={Wang, Qi and Boudreau, Claire and Luo, Qixing and Tan, Pang-Ning and Zhou, Jiayu},
  booktitle={Proceedings of the 2019 SIAM International Conference on Data Mining},
  pages={37--45},
  year={2019},
  organization={SIAM}
}

@inproceedings{alemi2016deep,
  title={Deep variational information bottleneck},
  author={Alemi, Alexander A and Fischer, Ian and Dillon, Joshua V and Murphy, Kevin},
  booktitle={5th International Conference on Learning Representations},
  year={2017}
}

@inproceedings{wan2021multi,
  title={Multi-View Information-Bottleneck Representation Learning},
  author={Wan, Zhibin and Zhang, Changqing and Zhu, Pengfei and Hu, Qinghua},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  pages={10085--10092},
  year={2021}
}

@article{zhang2016multi,
  title={Multi-view dimensionality reduction via canonical random correlation analysis},
  author={Zhang, Yanyan and Zhang, Jianchun and Pan, Zhisong and Zhang, Daoqiang},
  journal={Frontiers of Computer Science},
  volume={10},
  number={5},
  pages={856--869},
  year={2016},
  publisher={Springer}
}

@inproceedings{zhang2020learning,
  title={Learning invariant representations for reinforcement learning without reconstruction},
  author={Zhang, Amy and McAllister, Rowan and Calandra, Roberto and Gal, Yarin and Levine, Sergey},
  booktitle={9th International Conference on Learning Representations},
  year={2021}
}

@article{ferns2011bisimulation,
  title={Bisimulation metrics for continuous Markov decision processes},
  author={Ferns, Norm and Panangaden, Prakash and Precup, Doina},
  journal={SIAM Journal on Computing},
  volume={40},
  number={6},
  pages={1662--1714},
  year={2011},
  publisher={SIAM}
}

@inproceedings{laskin2020reinforcement,
  title={Reinforcement learning with augmented data},
  author={Laskin, Michael and Lee, Kimin and Stooke, Adam and Pinto, Lerrel and Abbeel, Pieter and Srinivas, Aravind},
  booktitle={Advances in Neural Information Processing Systems 33},
  year={2020}
}

@inproceedings{lee2020predictive,
  title={Predictive information accelerates learning in rl},
  author={Lee, Kuang-Huei and Fischer, Ian and Liu, Anthony and Guo, Yijie and Lee, Honglak and Canny, John and Guadarrama, Sergio},
  booktitle={Advances in Neural Information Processing Systems 33},
  year={2020}
}

@inproceedings{bachman2019learning,
  title={Learning representations by maximizing mutual information across views},
  author={Bachman, Philip and Hjelm, R Devon and Buchwalter, William},
  booktitle={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@inproceedings{wang2021residual,
  title={Residual Relaxation for Multi-view Representation Learning},
  author={Wang, Yifei and Geng, Zhengyang and Jiang, Feng and Li, Chuming and Wang, Yisen and Yang, Jiansheng and Lin, Zhouchen},
  booktitle={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

@inproceedings{haarnoja2018soft,
  title={Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor},
  author={Haarnoja, Tuomas and Zhou, Aurick and Abbeel, Pieter and Levine, Sergey},
  booktitle={International Conference on Machine Learning},
  pages={1861--1870},
  year={2018},
  organization={PMLR}
}

@inproceedings{ziebart2008maximum,
  title={Maximum entropy inverse reinforcement learning.},
  author={Ziebart, Brian D and Maas, Andrew L and Bagnell, J Andrew and Dey, Anind K and others},
  booktitle={Aaai},
  volume={8},
  pages={1433--1438},
  year={2008},
  organization={Chicago, IL, USA}
}

@book{cover1999elements,
  title={Elements of information theory},
  author={Cover, Thomas M},
  year={1999},
  publisher={John Wiley \& Sons}
}

@inproceedings{kingma2014auto,
  title={Auto-encoding variational bayes},
  author={Kingma, Diederik P and Welling, Max},
  booktitle={2nd International Conference on Learning Representations},
  year={2014}
}

@article{shapiro2003monte,
  title={Monte Carlo sampling methods},
  author={Shapiro, Alexander},
  journal={Handbooks in operations research and management science},
  volume={10},
  pages={353--425},
  year={2003},
  publisher={Elsevier}
}

@article{kay2017kinetics,
  title={The kinetics human action video dataset},
  author={Kay, Will and Carreira, Joao and Simonyan, Karen and Zhang, Brian and Hillier, Chloe and Vijayanarasimhan, Sudheendra and Viola, Fabio and Green, Tim and Back, Trevor and Natsev, Paul and others},
  journal={arXiv preprint arXiv:1705.06950},
  year={2017}
}

@inproceedings{yarats2021improving,
  title={Improving sample efficiency in model-free reinforcement learning from images},
  author={Yarats, Denis and Zhang, Amy and Kostrikov, Ilya and Amos, Brandon and Pineau, Joelle and Fergus, Rob},
  booktitle={Thirty-Fifth {AAAI} Conference on Artificial Intelligence},
  pages={10674--10681},
  year={2021}
}

@inproceedings{strehl2006pac,
  title={PAC model-free reinforcement learning},
  author={Strehl, Alexander L and Li, Lihong and Wiewiora, Eric and Langford, John and Littman, Michael L},
  booktitle={Proceedings of the 23rd international conference on Machine learning},
  pages={881--888},
  year={2006}
}

@book{kakade2003sample,
  title={On the sample complexity of reinforcement learning},
  author={Kakade, Sham Machandranath},
  year={2003},
  publisher={University of London, University College London (United Kingdom)}
}
