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Dibya Ghosh
Dibya Ghosh
UC Berkeley
Bestätigte E-Mail-Adresse bei berkeley.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Octo: An open-source generalist robot policy
OM Team, D Ghosh, H Walke, K Pertsch, K Black, O Mees, S Dasari, ...
arXiv preprint arXiv:2405.12213 2 (3), 7, 2024
310*2024
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 (ICLR 2021), arXiv …, 2021
234*2021
Variational inverse control with events: A general framework for data-driven reward definition
J Fu, A Singh, D Ghosh, L Yang, S Levine
Advances in neural information processing systems 31, 2018
1542018
Learning Actionable Representations with Goal-Conditioned Policies
D Ghosh, A Gupta, S Levine
International Conference on Learning Representations (ICLR 2019), 2019
1482019
Why generalization in rl is difficult: Epistemic pomdps and implicit partial observability
D Ghosh, J Rahme, A Kumar, A Zhang, RP Adams, S Levine
Advances in neural information processing systems 34, 25502-25515, 2021
1402021
Divide-and-conquer reinforcement learning
D Ghosh, A Singh, A Rajeswaran, V Kumar, S Levine
International Conference on Learning Representations (ICLR 2018), 2018
1312018
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
A Kumar, R Agarwal, D Ghosh, S Levine
International Conference on Learning Representations (ICLR 2021), 2021
1252021
Hiql: Offline goal-conditioned rl with latent states as actions
S Park, D Ghosh, B Eysenbach, S Levine
Advances in Neural Information Processing Systems 36, 34866-34891, 2023
572023
Representations for stable off-policy reinforcement learning
D Ghosh, MG Bellemare
International Conference on Machine Learning, 3556-3565, 2020
552020
Offline rl policies should be trained to be adaptive
D Ghosh, A Ajay, P Agrawal, S Levine
International Conference on Machine Learning, 7513-7530, 2022
532022
Reinforcement learning from passive data via latent intentions
D Ghosh, CA Bhateja, S Levine
International Conference on Machine Learning, 11321-11339, 2023
482023
An operator view of policy gradient methods
D Ghosh, M C Machado, N Le Roux
Advances in Neural Information Processing Systems 33, 3397-3406, 2020
292020
Robotic offline rl from internet videos via value-function pre-training
C Bhateja, D Guo, D Ghosh, A Singh, M Tomar, Q Vuong, Y Chebotar, ...
arXiv preprint arXiv:2309.13041, 2023
26*2023
On catastrophic interference in atari 2600 games
W Fedus, D Ghosh, JD Martin, MG Bellemare, Y Bengio, H Larochelle
arXiv preprint arXiv:2002.12499, 2020
192020
Distributionally adaptive meta reinforcement learning
A Ajay, A Gupta, D Ghosh, S Levine, P Agrawal
Advances in Neural Information Processing Systems 35, 25856-25869, 2022
172022
Accelerating exploration with unlabeled prior data
Q Li, J Zhang, D Ghosh, A Zhang, S Levine
Advances in Neural Information Processing Systems 36, 67434-67458, 2023
92023
What Do Learning Dynamics Reveal About Generalization in LLM Reasoning?
K Kang, A Setlur, D Ghosh, J Steinhardt, C Tomlin, S Levine, A Kumar
arXiv preprint arXiv:2411.07681, 2024
32024
Video-Guided Skill Discovery
M Tomar, D Ghosh, V Myers, A Dragan, ME Taylor, P Bachman, S Levine
ICML 2023 Workshop The Many Facets of Preference-Based Learning, 2023
22023
Reward Hacking vs. Reward Conquering: A Comparative Analysis in Layman’s Term
D Ghosh
Generative Evolutionary MAML: Decoupling Latent Space and Learning
D Ghosh
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