Dibya Ghosh

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 30

Top Topics

Fully Observable

Perceptual Aliasing

Reinforcement Learning

Top Venues

Publications

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)
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 (2024)
Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. CoRR (2023)
Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. NeurIPS (2023)
Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
Accelerating Exploration with Unlabeled Prior Data. CoRR (2023)
Dibya Ghosh, Chethan Bhateja, Sergey Levine
Reinforcement Learning from Passive Data via Latent Intentions. CoRR (2023)
Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine
Accelerating Exploration with Unlabeled Prior Data. NeurIPS (2023)
Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine
Reinforcement Learning from Passive Data via Latent Intentions. ICML (2023)
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 Pre-Training. CoRR (2023)
Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
Offline RL Policies Should be Trained to be Adaptive. CoRR (2022)
Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
Distributionally Adaptive Meta Reinforcement Learning. CoRR (2022)
Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine
Offline RL Policies Should Be Trained to be Adaptive. ICML (2022)
Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
Distributionally Adaptive Meta Reinforcement Learning. NeurIPS (2022)
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)
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. ICLR (2021)
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)
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 (2021)
Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
An operator view of policy gradient methods. NeurIPS (2020)
William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle
On Catastrophic Interference in Atari 2600 Games. CoRR (2020)
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning. CoRR (2020)
Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
An operator view of policy gradient methods. CoRR (2020)
Dibya Ghosh, Marc G. Bellemare
Representations for Stable Off-Policy Reinforcement Learning. CoRR (2020)
Dibya Ghosh, Marc G. Bellemare
Representations for Stable Off-Policy Reinforcement Learning. ICML (2020)
Dibya Ghosh, Abhishek Gupta, Sergey Levine
Learning Actionable Representations with Goal Conditioned Policies. ICLR (Poster) (2019)
Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine
Learning To Reach Goals Without Reinforcement Learning. CoRR (2019)
Dibya Ghosh, Abhishek Gupta, Sergey Levine
Learning Actionable Representations with Goal-Conditioned Policies. CoRR (2018)
Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. CoRR (2018)
Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
Divide-and-Conquer Reinforcement Learning. ICLR (Poster) (2018)
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)
Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
Divide-and-Conquer Reinforcement Learning. CoRR (2017)