Rowan McAllister

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Sergey LevineUC Berkeley, Physical IntelligenceE-mail confirmado em eecs.berkeley.edu
Yarin GalAssociate Professor, University of OxfordE-mail confirmado em cs.ox.ac.uk
Nicholas RhinehartAssistant Professor, University of TorontoE-mail confirmado em utoronto.ca
Roberto CalandraProfessor, TU Dresden / Centre for Tactile Internet with Human-in-the-Loop (CeTI)E-mail confirmado em tu-dresden.de
Adrien GaidonAdjunct Professor, StanfordE-mail confirmado em stanford.edu
Kris KitaniCarnegie Mellon University, Meta FAIRE-mail confirmado em andrew.cmu.edu
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeE-mail confirmado em cam.ac.uk
Mark van der WilkAssociate Professor, University of OxfordE-mail confirmado em cs.ox.ac.uk
Blake WulfeMachine Learning Researcher, Toyota Research Institute (TRI)E-mail confirmado em tri.global
Joseph E. GonzalezProfessor of Computer Science, UC BerkeleyE-mail confirmado em berkeley.edu
Kurtland ChuaPrinceton UniversityE-mail confirmado em princeton.edu
Robert FitchSchool of Mechanical and Mechatronic Engineering, University of Technology SydneyE-mail confirmado em uts.edu.au
Thierry PeynotQueensland University of Technology (QUT)E-mail confirmado em qut.edu.au
Amar ShahPhD student, University of CambridgeE-mail confirmado em cam.ac.uk
Adrian WellerDirector of Research, Machine Learning, University of CambridgeE-mail confirmado em eng.cam.ac.uk
Roberto CipollaProfessor of Information Engineering, University of CambridgeE-mail confirmado em eng.cam.ac.uk
Alex KendallUniversity of CambridgeE-mail confirmado em cam.ac.uk
Jean MercatResearch scientist at Toyota Research InstituteE-mail confirmado em tri.global
Ashwin BalakrishnaGoogle DeepMindE-mail confirmado em google.com
Amy ZhangAssistant Professor of Electrical and Computer Engineering at University of Texas at AustinE-mail confirmado em austin.utexas.edu

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Rowan McAllister

Waymo

E-mail confirmado em waymo.com - Página inicial

Reinforcement Learning Robotics Machine Learning Autonomous Vehicles


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Deep reinforcement learning in a handful of trials using probabilistic dynamics models K Chua, R Calandra, R McAllister, S Levine Advances in Neural Information Processing Systems, 4754-4765, 2018	1630	2018
Learning invariant representations for reinforcement learning without reconstruction A Zhang, R McAllister, R Calandra, Y Gal, S Levine International Conference on Learning Representations, 2020	551	2020
PRECOG: Prediction conditioned on goals in visual multi-agent settings N Rhinehart, R McAllister, K Kitani, S Levine International Conference on Computer Vision, 2821-2830, 2019	456	2019
Concrete problems for autonomous vehicle safety: advantages of Bayesian deep learning R McAllister, Y Gal, A Kendall, M Van Der Wilk, A Shah, R Cipolla, ... International Joint Conferences on Artificial Intelligence, Inc., 2017	430*	2017
Improving PILCO with Bayesian neural network dynamics models Y Gal, R McAllister, CE Rasmussen Data-Efficient Machine Learning workshop, ICML 4, 2016	341	2016
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? A Filos, P Tigas, R McAllister, N Rhinehart, S Levine, Y Gal International Conference on Machine Learning, 2020	238	2020
Deep Imitative Models for Flexible Inference, Planning, and Control N Rhinehart, R McAllister, S Levine International Conference on Learning Representations, 2018	167	2018
Safety Augmented Value Estimation from Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks B Thananjeyan, A Balakrishna, U Rosolia, F Li, R McAllister, JE Gonzalez, ... IEEE Robotics and Automation Letters 5 (2), 3612-3619, 2020	129	2020
Model-Based Meta-Reinforcement Learning for Flight with Suspended Payloads S Belkhale, R Li, G Kahn, R McAllister, R Calandra, S Levine IEEE Robotics and Automation Letters, 2020	115	2020
Waymax: An accelerated, data-driven simulator for large-scale autonomous driving research C Gulino, J Fu, W Luo, G Tucker, E Bronstein, Y Lu, J Harb, X Pan, ... Advances in Neural Information Processing Systems 36, 7730-7742, 2023	103	2023
Data-efficient reinforcement learning in continuous state-action Gaussian-POMDPs R McAllister, CE Rasmussen Advances in Neural Information Processing Systems, 2040-2049, 2017	59*	2017
Robustness to out-of-distribution inputs via task-aware generative uncertainty R McAllister, G Kahn, J Clune, S Levine International Conference on Robotics and Automation, 2019	48	2019
Heterogeneous-agent trajectory forecasting incorporating class uncertainty B Ivanovic, KH Lee, P Tokmakov, B Wulfe, R Mcllister, A Gaidon, ... 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022	43	2022
Learned stochastic mobility prediction for planning with control uncertainty on unstructured terrain T Peynot, ST Lui, R McAllister, R Fitch, S Sukkarieh Journal of Field Robotics 31 (6), 969-995, 2014	43	2014
Contingencies from observations: Tractable contingency planning with learned behavior models N Rhinehart, J He, C Packer, MA Wright, R McAllister, JE Gonzalez, ... 2021 IEEE International Conference on Robotics and Automation (ICRA), 13663 …, 2021	37	2021
Hierarchical planning for self-reconfiguring robots using module kinematics R Fitch, R McAllister Distributed Autonomous Robotic Systems: The 10th International Symposium …, 2013	29	2013
Control-aware prediction objectives for autonomous driving R McAllister, B Wulfe, J Mercat, L Ellis, S Levine, A Gaidon 2022 International Conference on Robotics and Automation (ICRA), 01-08, 2022	28	2022
Dynamics-aware comparison of learned reward functions B Wulfe, A Balakrishna, L Ellis, J Mercat, R McAllister, A Gaidon arXiv preprint arXiv:2201.10081, 2022	21	2022
S2net: Stochastic sequential pointcloud forecasting X Weng, J Nan, KH Lee, R McAllister, A Gaidon, N Rhinehart, KM Kitani European Conference on Computer Vision, 549-564, 2022	20	2022
Outcome-driven reinforcement learning via variational inference TGJ Rudner, V Pong, R McAllister, Y Gal, S Levine Advances in Neural Information Processing Systems 34, 13045-13058, 2021	19	2021

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