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Denis Yarats
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2020 – today
- 2022
- [c18]Siddhant Haldar, Vaibhav Mathur, Denis Yarats, Lerrel Pinto:
Watch and Match: Supercharging Imitation with Regularized Optimal Transport. CoRL 2022: 32-43 - [c17]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. ICLR 2022 - [c16]Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel:
Unsupervised Reinforcement Learning with Contrastive Intrinsic Control. NeurIPS 2022 - [i20]Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto:
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning. CoRR abs/2201.13425 (2022) - [i19]Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel:
CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery. CoRR abs/2202.00161 (2022) - [i18]Siddhant Haldar, Vaibhav Mathur, Denis Yarats, Lerrel Pinto:
Watch and Match: Supercharging Imitation with Regularized Optimal Transport. CoRR abs/2206.15469 (2022) - 2021
- [c15]Jerry Ma, Denis Yarats:
On the Adequacy of Untuned Warmup for Adaptive Optimization. AAAI 2021: 8828-8836 - [c14]Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. AAAI 2021: 10674-10681 - [c13]Denis Yarats, Ilya Kostrikov, Rob Fergus:
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. ICLR 2021 - [c12]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Reinforcement Learning with Prototypical Representations. ICML 2021: 11920-11931 - [c11]Joanne Truong, Denis Yarats, Tianyu Li, Franziska Meier, Sonia Chernova, Dhruv Batra, Akshara Rai:
Learning Navigation Skills for Legged Robots with Learned Robot Embeddings. IROS 2021: 484-491 - [c10]Brandon Amos, Samuel Stanton, Denis Yarats, Andrew Gordon Wilson:
On the model-based stochastic value gradient for continuous reinforcement learning. L4DC 2021: 6-20 - [c9]Stefan Bauer, Manuel Wüthrich, Felix Widmaier, Annika Buchholz, Sebastian Stark, Anirudh Goyal, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vincent Berenz, Vaibhav Agrawal, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Takahiro Maeda
, Harshit Sikchi, Jilong Wang, Qingfeng Yao, Shuyu Yang, Robert McCarthy, Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Stephen J. Redmond, Bernhard Schölkopf:
Real Robot Challenge: A Robotics Competition in the Cloud. NeurIPS (Competition and Demos) 2021: 190-204 - [c8]Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel:
URLB: Unsupervised Reinforcement Learning Benchmark. NeurIPS Datasets and Benchmarks 2021 - [c7]Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus:
Automatic Data Augmentation for Generalization in Reinforcement Learning. NeurIPS 2021: 5402-5415 - [i17]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Reinforcement Learning with Prototypical Representations. CoRR abs/2102.11271 (2021) - [i16]Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto:
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. CoRR abs/2107.09645 (2021) - [i15]Stefan Bauer, Felix Widmaier, Manuel Wüthrich, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Charles B. Schaff, Takahiro Maeda, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Annika Buchholz, Sebastian Stark, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bernhard Schölkopf:
A Robot Cluster for Reproducible Research in Dexterous Manipulation. CoRR abs/2109.10957 (2021) - [i14]Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel:
URLB: Unsupervised Reinforcement Learning Benchmark. CoRR abs/2110.15191 (2021) - 2020
- [c6]Brandon Amos, Denis Yarats:
The Differentiable Cross-Entropy Method. ICML 2020: 291-302 - [i13]Ilya Kostrikov, Denis Yarats, Rob Fergus:
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. CoRR abs/2004.13649 (2020) - [i12]Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus:
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning. CoRR abs/2006.12862 (2020) - [i11]Brandon Amos, Samuel Stanton, Denis Yarats, Andrew Gordon Wilson:
On the model-based stochastic value gradient for continuous reinforcement learning. CoRR abs/2008.12775 (2020) - [i10]Joanne Truong, Denis Yarats, Tianyu Li, Franziska Meier, Sonia Chernova, Dhruv Batra, Akshara Rai:
Learning Navigation Skills for Legged Robots with Learned Robot Embeddings. CoRR abs/2011.12255 (2020)
2010 – 2019
- 2019
- [c5]Jerry Ma, Denis Yarats:
Quasi-hyperbolic momentum and Adam for deep learning. ICLR (Poster) 2019 - [c4]Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis:
Hierarchical Decision Making by Generating and Following Natural Language Instructions. NeurIPS 2019: 10025-10034 - [i9]Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis:
Hierarchical Decision Making by Generating and Following Natural Language Instructions. CoRR abs/1906.00744 (2019) - [i8]Brandon Amos, Denis Yarats:
The Differentiable Cross-Entropy Method. CoRR abs/1909.12830 (2019) - [i7]Edward Grefenstette, Brandon Amos, Denis Yarats, Phu Mon Htut, Artem Molchanov, Franziska Meier, Douwe Kiela, Kyunghyun Cho, Soumith Chintala:
Generalized Inner Loop Meta-Learning. CoRR abs/1910.01727 (2019) - [i6]Denis Yarats, Amy Zhang
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. CoRR abs/1910.01741 (2019) - [i5]Jerry Ma, Denis Yarats:
On the adequacy of untuned warmup for adaptive optimization. CoRR abs/1910.04209 (2019) - 2018
- [c3]Denis Yarats, Mike Lewis:
Hierarchical Text Generation and Planning for Strategic Dialogue. ICML 2018: 5587-5595 - [i4]Jerry Ma
Quasi-hyperbolic momentum and Adam for deep learning. CoRR abs/1810.06801 (2018) - 2017
- [c2]Mike Lewis, Denis Yarats, Yann N. Dauphin, Devi Parikh, Dhruv Batra:
Deal or No Deal? End-to-End Learning of Negotiation Dialogues. EMNLP 2017: 2443-2453 - [c1]Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin:
Convolutional Sequence to Sequence Learning. ICML 2017: 1243-1252 - [i3]Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin:
Convolutional Sequence to Sequence Learning. CoRR abs/1705.03122 (2017) - [i2]Mike Lewis, Denis Yarats, Yann N. Dauphin, Devi Parikh, Dhruv Batra:
Deal or No Deal? End-to-End Learning for Negotiation Dialogues. CoRR abs/1706.05125 (2017) - [i1]Denis Yarats, Mike Lewis:
Hierarchical Text Generation and Planning for Strategic Dialogue. CoRR abs/1712.05846 (2017)
Coauthor Index
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