Michael Janner

According to our database, Michael Janner authored at least 16 papers between 2017 and 2024.

Collaborative distances:

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

2024

H-GAP: Humanoid Control with a Generalist Planner.

Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Training Diffusion Models with Reinforcement Learning.

Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Deep Generative Models for Decision-Making and Control.

Michael Janner

CoRR, 2023

IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine

CoRR, 2023

Efficient Planning in a Compact Latent Action Space.

Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control.

Katie Kang, Paula Gradu, Jason J. Choi, Michael Janner, Claire J. Tomlin, Sergey Levine

Proceedings of the International Conference on Machine Learning, 2022

Planning with Diffusion for Flexible Behavior Synthesis.

Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine

Proceedings of the International Conference on Machine Learning, 2022

2021

Reinforcement Learning as One Big Sequence Modeling Problem.

Michael Janner, Qiyang Li, Sergey Levine

CoRR, 2021

Offline Reinforcement Learning as One Big Sequence Modeling Problem.

Michael Janner, Qiyang Li, Sergey Levine

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

2020

γ-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction.

Michael Janner, Igor Mordatch, Sergey Levine

CoRR, 2020

Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction.

Michael Janner, Igor Mordatch, Sergey Levine

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

2019

When to Trust Your Model: Model-Based Policy Optimization.

Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Reasoning About Physical Interactions with Object-Oriented Prediction and Planning.

Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu

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

Entity Abstraction in Visual Model-Based Reinforcement Learning.

Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2017

Self-Supervised Intrinsic Image Decomposition.

Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Causal and compositional generative models in online perception.

Ilker Yildirim, Michael Janner, Mario Belledonne, Christian Wallraven, Winrich Freiwald, Josh Tenenbaum

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017