Dibya Ghosh

According to our database, Dibya Ghosh authored at least 16 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Robotic Offline RL from Internet Videos via Value-Function Pre-Training.

Chethan Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar

CoRR, 2023

HIQL: Offline Goal-Conditioned RL with Latent States as Actions.

Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Accelerating Exploration with Unlabeled Prior Data.

Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reinforcement Learning from Passive Data via Latent Intentions.

Dibya Ghosh, Chethan Anand Bhateja, Sergey Levine

Proceedings of the International Conference on Machine Learning, 2023

2022

Distributionally Adaptive Meta Reinforcement Learning.

Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Offline RL Policies Should Be Trained to be Adaptive.

Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine

Proceedings of the International Conference on Machine Learning, 2022

2021

Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability.

Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning.

Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning to Reach Goals via Iterated Supervised Learning.

Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

On Catastrophic Interference in Atari 2600 Games.

William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle

CoRR, 2020

An operator view of policy gradient methods.

Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Representations for Stable Off-Policy Reinforcement Learning.

Dibya Ghosh, Marc G. Bellemare

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Learning To Reach Goals Without Reinforcement Learning.

Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine

CoRR, 2019

Learning Actionable Representations with Goal Conditioned Policies.

Dibya Ghosh, Abhishek Gupta, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition.

Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Divide-and-Conquer Reinforcement Learning.

Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine

Proceedings of the 6th International Conference on Learning Representations, 2018