Dibya Ghosh - RankMe

36 papers A* 13Journal 20Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ViVa: Video-Trained Value Functions for Guiding Online RL from Diverse Data. CoRR Nitish Dashora, Dibya Ghosh, Sergey Levine
2025	J	`jnl`	Visual Pre-Training on Unlabeled Images using Reinforcement Learning. CoRR Dibya Ghosh, Sergey Levine
2025	A*	`conf`	What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning? ICML Katie Kang, Amrith Setlur, Dibya Ghosh, Jacob Steinhardt, Claire J. Tomlin, Sergey Levine, Aviral Kumar
2025	J	`jnl`	π CoRR Physical Intelligence, Kevin Black, Noah Brown, James Darpinian, Karan Dhabalia, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Manuel Y. Galliker, Dibya Ghosh, Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, Liyiming Ke, Devin LeBlanc, Sergey Levine, Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Allen Z. Ren, Lucy Xiaoyang Shi, Laura Smith, Jost Tobias Springenberg, Kyle Stachowicz, James Tanner, Quan Vuong, Homer Walke, Anna Walling, Haohuan Wang, Lili Yu, Ury Zhilinsky
2024	—	`conf`	Octo: An Open-Source Generalist Robot Policy. Robotics: Science and Systems Dibya Ghosh, Homer Rich Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Quan Vuong, Ted Xiao, Pannag R. Sanketi, Dorsa Sadigh, Chelsea Finn, Sergey Levine
2024	J	`jnl`	Octo: An Open-Source Generalist Robot Policy. CoRR 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
2024	A*	`conf`	Robotic Offline RL from Internet Videos via Value-Function Learning. ICRA Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar
2024	J	`jnl`	What Do Learning Dynamics Reveal About Generalization in LLM Reasoning? CoRR Katie Kang, Amrith Setlur, Dibya Ghosh, Jacob Steinhardt, Claire J. Tomlin, Sergey Levine, Aviral Kumar
2023	A*	`conf`	Accelerating Exploration with Unlabeled Prior Data. NeurIPS Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
2023	J	`jnl`	Accelerating Exploration with Unlabeled Prior Data. CoRR Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
2023	A*	`conf`	HIQL: Offline Goal-Conditioned RL with Latent States as Actions. NeurIPS Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
2023	J	`jnl`	HIQL: Offline Goal-Conditioned RL with Latent States as Actions. CoRR Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
2023	A*	`conf`	Reinforcement Learning from Passive Data via Latent Intentions. ICML Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine
2023	J	`jnl`	Reinforcement Learning from Passive Data via Latent Intentions. CoRR Dibya Ghosh, Chethan Bhateja, Sergey Levine
2023	J	`jnl`	Robotic Offline RL from Internet Videos via Value-Function Pre-Training. CoRR Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar
2022	A*	`conf`	Distributionally Adaptive Meta Reinforcement Learning. NeurIPS Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
2022	J	`jnl`	Distributionally Adaptive Meta Reinforcement Learning. CoRR Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
2022	A*	`conf`	Offline RL Policies Should Be Trained to be Adaptive. ICML Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
2022	J	`jnl`	Offline RL Policies Should be Trained to be Adaptive. CoRR Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
2021	A*	`conf`	Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. ICLR Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
2021	A*	`conf`	Learning to Reach Goals via Iterated Supervised Learning. ICLR Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine
2021	A*	`conf`	Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. NeurIPS Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine
2021	J	`jnl`	Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability. CoRR Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine
2020	A*	`conf`	An operator view of policy gradient methods. NeurIPS Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
2020	J	`jnl`	An operator view of policy gradient methods. CoRR Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
2020	J	`jnl`	Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. CoRR Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
2020	J	`jnl`	On Catastrophic Interference in Atari 2600 Games. CoRR William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle
2020	A*	`conf`	Representations for Stable Off-Policy Reinforcement Learning. ICML Dibya Ghosh, Marc G. Bellemare
2020	J	`jnl`	Representations for Stable Off-Policy Reinforcement Learning. CoRR Dibya Ghosh, Marc G. Bellemare
2019	—	`conf`	Learning Actionable Representations with Goal Conditioned Policies. ICLR (Poster) Dibya Ghosh, Abhishek Gupta, Sergey Levine
2019	J	`jnl`	Learning To Reach Goals Without Reinforcement Learning. CoRR Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine
2018	—	`conf`	Divide-and-Conquer Reinforcement Learning. ICLR (Poster) Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
2018	J	`jnl`	Learning Actionable Representations with Goal-Conditioned Policies. CoRR Dibya Ghosh, Abhishek Gupta, Sergey Levine
2018	A*	`conf`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. NeurIPS Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2018	J	`jnl`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. CoRR Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2017	J	`jnl`	Divide-and-Conquer Reinforcement Learning. CoRR Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine