追蹤
Benjamin Eysenbach
Benjamin Eysenbach
在 princeton.edu 的電子郵件地址已通過驗證 - 首頁
標題
引用次數
引用次數
年份
Diversity Is All You Need: Learning Skills without a Reward Function
B Eysenbach, A Gupta, J Ibarz, S Levine
International Conference on Learning Representations, 2019
10952019
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
B Eysenbach, R Salakhutdinov, S Levine
Advances in Neural Information Processing Systems, 15246-15257, 2019
3082019
Efficient Exploration via State Marginal Matching
L Lee, B Eysenbach, E Parisotto, E Xing, S Levine, R Salakhutdinov
arXiv preprint arXiv:1906.05274, 2019
2572019
Learning to Reach Goals via Iterated Supervised Learning
D Ghosh, A Gupta, A Reddy, J Fu, C Devin, B Eysenbach, S Levine
International Conference on Learning Representations, 2021
177*2021
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
JD Co-Reyes, YX Liu, A Gupta, B Eysenbach, P Abbeel, S Levine
International Conference on Machine Learning, 2018
1672018
RvS: What is Essential for Offline RL via Supervised Learning?
S Emmons, B Eysenbach, I Kostrikov, S Levine
International Conference on Learning Representations, 2022
1662022
Clustervision: Visual Supervision of Unsupervised Clustering
BC Kwon, B Eysenbach, J Verma, K Ng, C De Filippi, WF Stewart, A Perer
IEEE transactions on visualization and computer graphics 24 (1), 142-151, 2017
1552017
Maximum Entropy RL (Provably) Solves Some Robust RL Problems
B Eysenbach, S Levine
International Conference on Learning Representations, 2022
1542022
Leave No Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning
B Eysenbach, S Gu, J Ibarz, S Levine
International Conference on Learning Representations, 2018
1542018
Learning to be Safe: Deep RL with a Safety Critic
K Srinivasan, B Eysenbach, S Ha, J Tan, C Finn
arXiv preprint arXiv:2010.14603, 2020
1422020
Unsupervised Meta-Learning for Reinforcement Learning
A Gupta, B Eysenbach, C Finn, S Levine
arXiv preprint arXiv:1806.04640, 2018
1372018
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
Y Chebotar, K Hausman, Y Lu, T Xiao, D Kalashnikov, J Varley, A Irpan, ...
International Conference on Machine Learning, 2021
1352021
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs
T Ni, B Eysenbach, S Levine, R Salakhutdinov
International Conference on Machine Learning, 2022
100*2022
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
B Eysenbach, X Geng, S Levine, R Salakhutdinov
Advances in Neural Information Processing Systems 33, 2020
1002020
Contrastive Learning as Goal-Conditioned Reinforcement Learning
B Eysenbach, T Zhang, S Levine, RR Salakhutdinov
Advances in Neural Information Processing Systems 35, 35603-35620, 2022
872022
ViNG: Learning open-world navigation with visual goals
D Shah, B Eysenbach, G Kahn, N Rhinehart, S Levine
International Conference on Robotics and Automation, 13215-13222, 2021
752021
Unsupervised Curricula for Visual Meta-Reinforcement Learning
A Jabri, K Hsu, A Gupta, B Eysenbach, S Levine, C Finn
Advances in Neural Information Processing Systems, 2019
702019
f-IRL: Inverse Reinforcement Learning via State Marginal Matching
T Ni, H Sikchi, Y Wang, T Gupta, L Lee, B Eysenbach
Conference on Robot Learning, 2020
692020
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
B Eysenbach, S Chaudhari, S Asawa, S Levine, R Salakhutdinov
International Conference on Learning Representations, 2020
692020
C-Learning: Learning to Achieve Goals via Recursive Classification
B Eysenbach, R Salakhutdinov, S Levine
International Conference on Learning Representations, 2021
662021
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