R. McAllister

发表

Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models

Sergey Levine, Rowan McAllister, Roberto Calandra, 2018, NeurIPS.

Improving PILCO with Bayesian Neural Network Dynamics Models

C. Rasmussen, Rowan McAllister, R. McAllister, 2016 .

Learning Invariant Representations for Reinforcement Learning without Reconstruction

S. Levine, Rowan McAllister, R. Calandra, 2020, ICLR.

Model-Based Meta-Reinforcement Learning for Flight With Suspended Payloads

S. Levine, R. Calandra, G. Kahn, 2020, IEEE Robotics and Automation Letters.

Learned Stochastic Mobility Prediction for Planning with Control Uncertainty on Unstructured Terrain

Thierry Peynot, Robert Fitch, Salah Sukkarieh, 2014, J. Field Robotics.

Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks

S. Levine, Ken Goldberg, Rowan McAllister, 2019, IEEE Robotics and Automation Letters.

Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?

Sergey Levine, Nicholas Rhinehart, Rowan McAllister, 2020, ICML.

Robust Imitative Planning: Planning from Demonstrations Under Uncertainty

S. Levine, Rowan McAllister, P. Tigas, 2019 .

Deep Imitative Models for Flexible Inference, Planning, and Control pdf

Sergey Levine, Nicholas Rhinehart, Rowan McAllister, 2018, ICLR.

Bayesian learning for data-efficient control

Rowan McAllister, R. McAllister, 2017 .

Data-Efficient Reinforcement Learning in Continuous-State POMDPs pdf

Carl E. Rasmussen, Rowan McAllister, C. Rasmussen, 2016, ArXiv.

Motion planning and stochastic control with experimental validation on a planetary rover

Thierry Peynot, Robert Fitch, Salah Sukkarieh, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Outcome-Driven Reinforcement Learning via Variational Inference

Tim G. J. Rudner, Vitchyr H. Pong, S. Levine, 2021, NeurIPS.

Sociotechnical Specification for the Broader Impacts of Autonomous Vehicles

Aaron J. Snoswell, Rowan McAllister, Cathy Wu, 2022, ArXiv.

Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty

Sergey Levine, Rowan McAllister, Jeff Clune, 2018, 2019 International Conference on Robotics and Automation (ICRA).

Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty

Adrien Gaidon, M. Pavone, Kuan-Hui Lee, 2021, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

PRECOG: PREdiction Conditioned on Goals in Visual Multi-Agent Settings

Sergey Levine, Nicholas Rhinehart, Rowan McAllister, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

PRECOG : PREdictions Conditioned On Goals in Visual Multi-Agent Scenarios

Kris M. Kitani, S. Levine, Rowan McAllister, 2019 .

Control-Aware Prediction Objectives for Autonomous Driving

S. Levine, Rowan McAllister, Adrien Gaidon, 2022, 2022 International Conference on Robotics and Automation (ICRA).

Autonomous Vehicle Vision 2021: ICCV Workshop Summary

Rowan McAllister, F. Yu, Nemanja Djuric, 2021, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models

Matthew A. Wright, S. Levine, Nicholas Rhinehart, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning

Roberto Cipolla, Mark van der Wilk, Adrian Weller, 2017, IJCAI.

RAP: Risk-Aware Prediction for Robust Planning

Rowan McAllister, Adrien Gaidon, Blake Wulfe, 2022, CoRL.

Dynamics-Aware Comparison of Learned Reward Functions

Ashwin Balakrishna, Rowan McAllister, Adrien Gaidon, 2022, ICLR.

Hierarchical Planning for Self-reconfiguring Robots Using Module Kinematics

Robert Fitch, Rowan McAllister, R. Fitch, 2010, DARS.

S2Net: Stochastic Sequential Pointcloud Forecasting

Nicholas Rhinehart, Adrien Gaidon, Kris Kitani, 2022, ECCV.

Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty

Matthew A. Wright, S. Levine, Nicholas Rhinehart, 2022, Conference on Robot Learning.

Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs

Carl E. Rasmussen, Rowan McAllister, C. Rasmussen, 2017, NIPS.

Concrete Problems for Safety in Autonomous Vehicles through Bayesian Deep Learning

Mark van der Wilk, Rowan McAllister, Y. Gal, 2017 .

CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting

Nicholas Rhinehart, R. McAllister, Jiezhi Yang, 2024, ArXiv.

Learning Invariant Representations for Reinforcement Learning without Reconstruction pdf

Rowan McAllister, Yarin Gal, Roberto Calandra, 2020, ICLR.

Resilient Navigation through Probabilistic Modality Reconfiguration

Thierry Peynot, Robert Fitch, Alen Alempijevic, 2012, IAS.