Causal and compositional generative models in online perception. - Ilker Yildirim; Michael Janner; Mario Belledonne; Christian Wallraven; Winrich Freiwald; Josh Tenenbaum 001 (CogSci, 2017)

Self-Supervised Intrinsic Image Decomposition. - Michael Janner; Jiajun Wu 001; Tejas D. Kulkarni; Ilker Yildirim; Josh Tenenbaum 001 (NIPS, 2017)

Entity Abstraction in Visual Model-Based Reinforcement Learning. - Rishi Veerapaneni; John D. Co-Reyes; Michael Chang 003; Michael Janner; Chelsea Finn; Jiajun Wu 001; Joshua B. Tenenbaum; Sergey Levine (CoRL, 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 001 (ICLR (Poster), 2019)

When to Trust Your Model: Model-Based Policy Optimization. - Michael Janner; Justin Fu; Marvin Zhang; Sergey Levine (NeurIPS, 2019)

Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. - Michael Janner; Igor Mordatch; Sergey Levine (NeurIPS, 2020)

γ-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. - Michael Janner; Igor Mordatch; Sergey Levine (CoRR, 2020)

Offline Reinforcement Learning as One Big Sequence Modeling Problem. - Michael Janner; Qiyang Li; Sergey Levine (NeurIPS, 2021)

Reinforcement Learning as One Big Sequence Modeling Problem. - Michael Janner; Qiyang Li; Sergey Levine (CoRR, 2021)

Planning with Diffusion for Flexible Behavior Synthesis. - Michael Janner; Yilun Du; Joshua B. Tenenbaum; Sergey Levine (ICML, 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 (ICML, 2022)

Efficient Planning in a Compact Latent Action Space. - Zhengyao Jiang; Tianjun Zhang; Michael Janner; Yueying Li; Tim Rocktäschel; Edward Grefenstette; Yuandong Tian (ICLR, 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)

Deep Generative Models for Decision-Making and Control. - Michael Janner (CoRR, 2023)

Training Diffusion Models with Reinforcement Learning. - Kevin Black; Michael Janner; Yilun Du; Ilya Kostrikov; Sergey Levine (ICLR, 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 (ICLR, 2024)