McAllister, Rowan

10 publications

ECCV 2024 CARFF: Conditional Auto-Encoded Radiance Field for 3D Scene Forecasting Jiezhi Yang, Khushi P Desai, Charles Packer, Harshil Bhatia, Nicholas Rhinehart, Rowan McAllister, Joseph E Gonzalez

NeurIPS 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, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, Benjamin Sapp

ECCV 2022 S2Net: Stochastic Sequential Pointcloud Forecasting Xinshuo Weng, Junyu Nan, Kuan-Hui Lee, Rowan McAllister, Adrien Gaidon, Nicholas Rhinehart, Kris M. Kitani

ICCVW 2021 Autonomous Vehicle Vision 2021: ICCV Workshop Summary Rui Fan, Nemanja Djuric, Fisher Yu, Rowan McAllister, Ioannis Pitas

NeurIPS 2021 Outcome-Driven Reinforcement Learning via Variational Inference Tim G. J. Rudner, Vitchyr Pong, Rowan McAllister, Yarin Gal, Sergey Levine

ICML 2020 Can Autonomous Vehicles Identify, Recover from, and Adapt to Distribution Shifts? Angelos Filos, Panagiotis Tigkas, Rowan Mcallister, Nicholas Rhinehart, Sergey Levine, Yarin Gal

ICLR 2020 Deep Imitative Models for Flexible Inference, Planning, and Control Nicholas Rhinehart, Rowan McAllister, Sergey Levine

NeurIPS 2018 Deep Reinforcement Learning in a Handful of Trials Using Probabilistic Dynamics Models Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine

IJCAI 2017 Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller

NeurIPS 2017 Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs Rowan McAllister, Carl Edward Rasmussen