Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. - Maximilian Igl; Daewoo Kim; Alex Kuefler; Paul Mougin; Punit Shah; Kyriacos Shiarlis; Dragomir Anguelov; Mark Palatucci; Brandyn White; Shimon Whiteson (ICRA, 2022)

Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. - Eli Bronstein; Mark Palatucci; Dominik Notz; Brandyn White; Alex Kuefler; Yiren Lu 001; Supratik Paul; Payam Nikdel; Paul Mougin; Hongge Chen; Justin Fu; Austin Abrams; et al. (IROS, 2022)

Hierarchical Imitation Learning for Stochastic Environments. - Maximilian Igl; Punit Shah; Paul Mougin; Sirish Srinivasan; Tarun Gupta 002; Brandyn White; Kyriacos Shiarlis; Shimon Whiteson (IROS, 2023)

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. - Cole Gulino; Justin Fu; Wenjie Luo; George Tucker; Eli Bronstein; Yiren Lu 001; Jean Harb; Xinlei Pan; Yan Wang 051; Xiangyu Chen 007; John D. Co-Reyes; Rishabh Agarwal; et al. (NeurIPS, 2023)

The Waymo Open Sim Agents Challenge. - Nico Montali; John Lambert; Paul Mougin; Alex Kuefler; Nicholas Rhinehart; Michelle Li; Cole Gulino; Tristan Emrich; Zoey Yang; Shimon Whiteson; Brandyn White; Dragomir Anguelov (NeurIPS, 2023)

UniGen: Unified Modeling of Initial Agent States and Trajectories for Generating Autonomous Driving Scenarios. - Reza Mahjourian; Rongbing Mu; Valerii Likhosherstov; Paul Mougin; Xiukun Huang; João V. Messias; Shimon Whiteson (ICRA, 2024)