Rowan McAllister

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 35

Top Venues

CoRR

ICRA

NeurIPS

IEEE Robotics Autom. Lett.

University of Cambridge, UK (PHD)

Education History

University of Cambridge, UK

PHD

Publications

Jiezhi Yang, Khushi Desai, Charles Packer, Harshil Bhatia, Nicholas Rhinehart, Rowan McAllister, Joseph Gonzalez
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting. CoRR (2024)
Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, Benjamin Sapp
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. CoRR (2023)
Fernando Castañeda, Haruki Nishimura, Rowan McAllister, Koushil Sreenath, Adrien Gaidon
In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States. CoRR (2023)
Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, Benjamin Sapp
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. NeurIPS (2023)
Haruki Nishimura, Jean Mercat, Blake Wulfe, Rowan McAllister, Adrien Gaidon
RAP: Risk-Aware Prediction for Robust Planning. CoRR (2022)
Xinshuo Weng, Junyu Nan, Kuan-Hui Lee, Rowan McAllister, Adrien Gaidon, Nicholas Rhinehart, Kris M. Kitani
S2Net: Stochastic Sequential Pointcloud Forecasting. ECCV (27) (2022)
Thomas Krendl Gilbert, Aaron J. Snoswell, Michael Dennis, Rowan McAllister, Cathy Wu
Sociotechnical Specification for the Broader Impacts of Autonomous Vehicles. CoRR (2022)
Blake Wulfe, Ashwin Balakrishna, Logan Ellis, Jean Mercat, Rowan McAllister, Adrien Gaidon
Dynamics-Aware Comparison of Learned Reward Functions. CoRR (2022)
Rowan McAllister, Blake Wulfe, Jean Mercat, Logan Ellis, Sergey Levine, Adrien Gaidon
Control-Aware Prediction Objectives for Autonomous Driving. CoRR (2022)
Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Rowan McAllister, Adrien Gaidon, Marco Pavone
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty. IROS (2022)
Rowan McAllister, Blake Wulfe, Jean Mercat, Logan Ellis, Sergey Levine, Adrien Gaidon
Control-Aware Prediction Objectives for Autonomous Driving. ICRA (2022)
Tim G. J. Rudner, Vitchyr H. Pong, Rowan McAllister, Yarin Gal, Sergey Levine
Outcome-Driven Reinforcement Learning via Variational Inference. CoRR (2021)
Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Rowan McAllister, Adrien Gaidon, Marco Pavone
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty. CoRR (2021)
Tim G. J. Rudner, Vitchyr Pong, Rowan McAllister, Yarin Gal, Sergey Levine
Outcome-Driven Reinforcement Learning via Variational Inference. NeurIPS (2021)
Rui Fan, Nemanja Djuric, Fisher Yu, Rowan McAllister, Ioannis Pitas
Autonomous Vehicle Vision 2021: ICCV Workshop Summary. ICCVW (2021)
Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine
Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models. CoRR (2021)
Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine
Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models. ICRA (2021)
Suneel Belkhale, Rachel Li, Gregory Kahn, Rowan McAllister, Roberto Calandra, Sergey Levine
Model-Based Meta-Reinforcement Learning for Flight With Suspended Payloads. IEEE Robotics Autom. Lett. 6 (2) (2021)
Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? CoRR (2020)
Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? ICML (2020)
Nicholas Rhinehart, Rowan McAllister, Sergey Levine
Deep Imitative Models for Flexible Inference, Planning, and Control. ICLR (2020)
Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg
Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks. IEEE Robotics Autom. Lett. 5 (2) (2020)
Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Learning Invariant Representations for Reinforcement Learning without Reconstruction. CoRR (2020)
Suneel Belkhale, Rachel Li, Gregory Kahn, Rowan McAllister, Roberto Calandra, Sergey Levine
Model-Based Meta-Reinforcement Learning for Flight with Suspended Payloads. CoRR (2020)
Nicholas Rhinehart, Rowan McAllister, Kris Kitani, Sergey Levine
PRECOG: PREdiction Conditioned on Goals in Visual Multi-Agent Settings. ICCV (2019)
Rowan McAllister, Gregory Kahn, Jeff Clune, Sergey Levine
Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty. ICRA (2019)
Nicholas Rhinehart, Rowan McAllister, Kris M. Kitani, Sergey Levine
PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings. CoRR (2019)
Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg
Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations. CoRR (2019)
Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models. CoRR (2018)
Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models. NeurIPS (2018)
Rowan McAllister, Gregory Kahn, Jeff Clune, Sergey Levine
Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty. CoRR (2018)
Nicholas Rhinehart, Rowan McAllister, Sergey Levine
Deep Imitative Models for Flexible Inference, Planning, and Control. CoRR (2018)
Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller
Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning. IJCAI (2017)
Rowan McAllister, Carl Edward Rasmussen
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs. NIPS (2017)
Rowan McAllister, Carl Edward Rasmussen
Data-Efficient Reinforcement Learning in Continuous-State POMDPs. CoRR (2016)
Thierry Peynot, Sin-Ting Lui, Rowan McAllister, Robert Fitch, Salah Sukkarieh
Learned Stochastic Mobility Prediction for Planning with Control Uncertainty on Unstructured Terrain. J. Field Robotics 31 (6) (2014)
Rowan McAllister, Thierry Peynot, Robert Fitch, Salah Sukkarieh
Motion planning and stochastic control with experimental validation on a planetary rover. IROS (2012)
Thierry Peynot, Robert Fitch, Rowan McAllister, Alen Alempijevic
Resilient Navigation through Probabilistic Modality Reconfiguration. IAS (2) (2012)
Robert Fitch, Rowan McAllister
Hierarchical Planning for Self-reconfiguring Robots Using Module Kinematics. DARS (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rowan McAllister