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Self-supervised representation learning has achieved remarkable success in recent years.
Making the world differentiable: On using fully recurrent self-supervised neural networks for dynamic reinforcement learning and planning in non-stationary environments
Jürgen Schmidhuber · 1990
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A possibility for implementing curiosity and boredom in model-building neural controllers
Jürgen Schmidhuber · 1991
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The scientist in the crib: Minds, brains, and how children learn
Alison Gopnik, Andrew N Meltzoff, and Patricia K Kuhl · 1999
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The development of embodied cognition: Six lessons from babies
Linda Smith and Michael Gasser · 2005
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No-regret reductions for imitation learning and structured prediction
Stéphane Ross, Geoffrey J. Gordon, and J. Andrew Bagnell · 2010
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Representation learning: A review and new perspectives
Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2013
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Learning to poke by poking: Experiential learning of intuitive physics
Pulkit Agrawal, Ashvin Nair, Pieter Abbeel, Jitendra Malik, and Sergey Levine · 2016
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Unifying count-based exploration and intrinsic motivation
Marc Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, and Remi Munos · 2016
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Adversarially learned inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Olivier Mastropietro, Alex Lamb, Martin Arjovsky, and Aaron Courville · 2016
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Vime: Variational information maximizing exploration
Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, and Pieter Abbeel · 2016
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Reinforcement learning with unsupervised auxiliary tasks, 2016
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z Leibo, David Silver, and Koray Kavukcuoglu · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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The curious robot: Learning visual representations via physical interactions
Lerrel Pinto, Dhiraj Gandhi, Yuanfeng Han, Yong-Lae Park, and Abhinav Gupta · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
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Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A Efros, and Trevor Darrell · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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#exploration: A study of count-based exploration for deep reinforcement learning
Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, OpenAI Xi Chen, Yan Duan, John Schulman, Filip DeTurck, and Pieter Abbeel · 2017
Cited alongside, same era.
On evaluation of embodied navigation agents, 2018
Peter Anderson, Angel Chang, Devendra Singh Chaplot, Alexey Dosovitskiy, Saurabh Gupta, Vladlen Koltun, Jana Kosecka, Jitendra Malik, Roozbeh Mottaghi, Manolis Savva, and Amir R. Zamir · 2018
Cited alongside, same era.
Large-scale study of curiosity-driven learning
Yuri Burda, Harri Edwards, Deepak Pathak, Amos Storkey, Trevor Darrell, and Alexei A Efros · 2018
Data-efficient image recognition with contrastive predictive coding
Olivier J Hénaff, Ali Razavi, Carl Doersch, SM Eslami, and Aaron van den Oord · 2019
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Habitat: A platform for embodied ai research, 2019
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, Devi Parikh, and Dhruv Batra · 2019
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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Dd-ppo: Learning near-perfect pointgoal navigators from 2.5 billion frames
Erik Wijmans, Abhishek Kadian, Ari Morcos, Stefan Lee, Irfan Essa, Devi Parikh, Manolis Savva, and Dhruv Batra · 2019
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Unsupervised state representation learning in atari, 2020
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Cited alongside, same era.
Exploration by random network distillation
Yuri Burda, Harrison Edwards, Amos Storkey, and Oleg Klimov · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Geometry guided convolutional neural networks for self-supervised video representation learning
Chuang Gan, Boqing Gong, Kun Liu, Hao Su, and Leonidas J Guibas · 2018
Cited alongside, same era.
Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
Cited alongside, same era.
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Cited alongside, same era.
Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, X Yu Stella, and Dahua Lin · 2018
Cited alongside, same era.
Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, and R Devon Hjelm · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Integrating egocentric localization for more realistic point-goal navigation agents
Samyak Datta, Oleksandr Maksymets, Judy Hoffman, Stefan Lee, Dhruv Batra, and Devi Parikh · 2020
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Noisy agents: Self-supervised exploration by predicting auditory events
Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, and Joshua B Tenenbaum · 2020
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Threedworld: A platform for interactive multi-modal physical simulation
Chuang Gan, Jeremy Schwartz, Seth Alter, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, et al · 2020
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Beyond the nav-graph: Vision-and-language navigation in continuous environments, 2020
Jacob Krantz, Erik Wijmans, Arjun Majumdar, Dhruv Batra, and Stefan Lee · 2020
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Data-efficient reinforcement learning with self-predictive representations, 2020
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, and Philip Bachman · 2020
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Curl: Contrastive unsupervised representations for reinforcement learning, 2020
Aravind Srinivas, Michael Laskin, and Pieter Abbeel · 2020
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Decoupling representation learning from reinforcement learning, 2020
Adam Stooke, Kimin Lee, Pieter Abbeel, and Michael Laskin · 2020
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Rethinking few-shot image classification: a good embedding is all you need?, 2020
Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, and Phillip Isola · 2020
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Auxiliary tasks speed up learning pointgoal navigation
Joel Ye, Dhruv Batra, Erik Wijmans, and Abhishek Das · 2020
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Chuang Gan, Siyuan Zhou, Jeremy Schwartz, Seth Alter, Abhishek Bhandwaldar, Dan Gutfreund, Daniel LK Yamins, James J DiCarlo, Josh McDermott, Antonio Torralba, et al · 2021
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Environment predictive coding for embodied agents
Santhosh K Ramakrishnan, Tushar Nagarajan, Ziad Al-Halah, and Kristen Grauman · 2021
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