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Dibya Ghosh
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2020 – today
- 2024
- [c14]Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar:
Robotic Offline RL from Internet Videos via Value-Function Learning. ICRA 2024: 16977-16984 - [i16]Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Pannag Sanketi, Quan Vuong, Ted Xiao, Dorsa Sadigh, Chelsea Finn, Sergey Levine:
Octo: An Open-Source Generalist Robot Policy. CoRR abs/2405.12213 (2024) - 2023
- [c13]Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine:
Reinforcement Learning from Passive Data via Latent Intentions. ICML 2023: 11321-11339 - [c12]Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine:
Accelerating Exploration with Unlabeled Prior Data. NeurIPS 2023 - [c11]Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine:
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. NeurIPS 2023 - [i15]Dibya Ghosh, Chethan Bhateja, Sergey Levine:
Reinforcement Learning from Passive Data via Latent Intentions. CoRR abs/2304.04782 (2023) - [i14]Seohong Park, Dibya Ghosh, Benjamin Eysenbach
, Sergey Levine:
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. CoRR abs/2307.11949 (2023) - [i13]Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong
Robotic Offline RL from Internet Videos via Value-Function Pre-Training. CoRR abs/2309.13041 (2023) - [i12]Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine:
Accelerating Exploration with Unlabeled Prior Data. CoRR abs/2311.05067 (2023) - 2022
- [c10]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should Be Trained to be Adaptive. ICML 2022: 7513-7530 - [c9]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. NeurIPS 2022 - [i11]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should be Trained to be Adaptive. CoRR abs/2207.02200 (2022) - [i10]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. CoRR abs/2210.03104 (2022) - 2021
- [c8]Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine:
Learning to Reach Goals via Iterated Supervised Learning. ICLR 2021 - [c7]Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine:
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. ICLR 2021 - [c6]Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine:
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. NeurIPS 2021: 25502-25515 - [i9]Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine:
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. CoRR abs/2107.06277 (2021) - 2020
- [c5]Dibya Ghosh, Marc G. Bellemare:
Representations for Stable Off-Policy Reinforcement Learning. ICML 2020: 3556-3565 - [c4]Dibya Ghosh, Marlos C. Machado
An operator view of policy gradient methods. NeurIPS 2020 - [i8]William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle:
On Catastrophic Interference in Atari 2600 Games. CoRR abs/2002.12499 (2020) - [i7]Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux:
An operator view of policy gradient methods. CoRR abs/2006.11266 (2020) - [i6]Dibya Ghosh, Marc G. Bellemare:
Representations for Stable Off-Policy Reinforcement Learning. CoRR abs/2007.05520 (2020) - [i5]Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine:
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. CoRR abs/2010.14498 (2020)
2010 – 2019
- 2019
- [c3]Dibya Ghosh, Abhishek Gupta, Sergey Levine:
Learning Actionable Representations with Goal Conditioned Policies. ICLR (Poster) 2019 - [i4]Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine:
Learning To Reach Goals Without Reinforcement Learning. CoRR abs/1912.06088 (2019) - 2018
- [c2]Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine:
Divide-and-Conquer Reinforcement Learning. ICLR (Poster) 2018 - [c1]Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine:
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. NeurIPS 2018: 8547-8556 - [i3]Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine:
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. CoRR abs/1805.11686 (2018) - [i2]Dibya Ghosh, Abhishek Gupta, Sergey Levine:
Learning Actionable Representations with Goal-Conditioned Policies. CoRR abs/1811.07819 (2018) - 2017
- [i1]Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine:
Divide-and-Conquer Reinforcement Learning. CoRR abs/1711.09874 (2017)
Coauthor Index
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