Control-Aware Representations for Model-based Reinforcement Learning. - Brandon Cui; Yinlam Chow; Mohammad Ghavamzadeh (ICLR, 2021)

Off-Belief Learning. - Hengyuan Hu; Adam Lerer; Brandon Cui; Luis Pineda; Noam Brown; Jakob N. Foerster (ICML, 2021)

Trajectory Diversity for Zero-Shot Coordination. - Andrei Lupu; Brandon Cui; Hengyuan Hu; Jakob N. Foerster (ICML, 2021)

Variational Model-based Policy Optimization. - Yinlam Chow; Brandon Cui; Moonkyung Ryu; Mohammad Ghavamzadeh (IJCAI, 2021)

K-level Reasoning for Zero-Shot Coordination in Hanabi. - Brandon Cui; Hengyuan Hu; Luis Pineda; Jakob N. Foerster (NeurIPS, 2021)

Learning Space Partitions for Path Planning. - Kevin Yang; Tianjun Zhang; Chris Cummins; Brandon Cui; Benoit Steiner; Linnan Wang; Joseph E. Gonzalez; Dan Klein 001; Yuandong Tian (NeurIPS, 2021)

Off-Belief Learning. - Hengyuan Hu; Adam Lerer; Brandon Cui; Luis Pineda; David J. Wu 002; Noam Brown; Jakob N. Foerster (CoRR, 2021)

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. - Chris Cummins; Bram Wasti; Jiadong Guo; Brandon Cui; Jason Ansel; Sahir Gomez; Somya Jain; Jia Liu; Olivier Teytaud; Benoit Steiner; Yuandong Tian; Hugh Leather (CGO, 2022)

Off-Team Learning. - Brandon Cui; Hengyuan Hu; Andrei Lupu; Samuel Sokota; Jakob N. Foerster (NeurIPS, 2022)

Self-Explaining Deviations for Coordination. - Hengyuan Hu; Samuel Sokota; David J. Wu 002; Anton Bakhtin; Andrei Lupu; Brandon Cui; Jakob N. Foerster (NeurIPS, 2022)

Adversarial Diversity in Hanabi. - Brandon Cui; Andrei Lupu; Samuel Sokota; Hengyuan Hu; David J. Wu 002; Jakob Nicolaus Foerster (ICLR, 2023)

Critique-out-Loud Reward Models. - Zachary Ankner; Mansheej Paul; Brandon Cui; Jonathan D. Chang; Prithviraj Ammanabrolu (CoRR, 2024)