Model-Based Reinforcement Learning via Latent-Space Collocation. - Oleh Rybkin; Chuning Zhu; Anusha Nagabandi; Kostas Daniilidis; Igor Mordatch; Sergey Levine (ICML, 2021)

Self-Supervised Reinforcement Learning that Transfers using Random Features. - Boyuan Chen 003; Chuning Zhu; Pulkit Agrawal 001; Kaiqing Zhang; Abhishek Gupta 004 (NeurIPS, 2023)

RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. - Chuning Zhu; Max Simchowitz; Siri Gadipudi; Abhishek Gupta 004 (NeurIPS, 2023)

ASID: Active Exploration for System Identification in Robotic Manipulation. - Marius Memmel; Andrew Wagenmaker; Chuning Zhu; Dieter Fox; Abhishek Gupta 004 (ICLR, 2024)

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. - Zhaoyi Zhou; Chuning Zhu; Runlong Zhou; Qiwen Cui; Abhishek Gupta 004; Simon Shaolei Du (ICLR, 2024)

Distributional Successor Features Enable Zero-Shot Policy Optimization. - Chuning Zhu; Xinqi Wang; Tyler Han; Simon S. Du; Abhishek Gupta 004 (NeurIPS, 2024)

Transferable Reinforcement Learning via Generalized Occupancy Models. - Chuning Zhu; Xinqi Wang; Tyler Han; Simon S. Du; Abhishek Gupta 004 (CoRR, 2024)

ASID: Active Exploration for System Identification in Robotic Manipulation. - Marius Memmel; Andrew Wagenmaker; Chuning Zhu; Patrick Yin; Dieter Fox; Abhishek Gupta 004 (CoRR, 2024)

Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets. - Chuning Zhu; Raymond Yu; Siyuan Feng 003; Benjamin Burchfiel; Paarth Shah; Abhishek Gupta 004 (CoRR, 2025)