Nicholas Rhinehart

According to our database, Nicholas Rhinehart authored at least 34 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigation.

James R. Han, Hugues Thomas, Jian Zhang, Nicholas Rhinehart, Timothy D. Barfoot

CoRR, 2024

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

Jiezhi Yang, Khushi Desai, Charles Packer, Harshil Bhatia, Nicholas Rhinehart, Rowan McAllister, Joseph E. Gonzalez

Proceedings of the Computer Vision - ECCV 2024, 2024

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Hybrid Imitative Planning with Geometric and Predictive Costs in Off-road Environments.

Nitish Dashora, Daniel Shin, Dhruv Shah, Henry A. Leopold, David D. Fan, Ali-Akbar Agha-Mohammadi, Nicholas Rhinehart, Sergey Levine

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

S2Net: Stochastic Sequential Pointcloud Forecasting.

Xinshuo Weng, Junyu Nan, Kuan-Hui Lee, Rowan McAllister, Adrien Gaidon, Nicholas Rhinehart, Kris M. Kitani

Proceedings of the Computer Vision - ECCV 2022, 2022

Offline Reinforcement Learning for Visual Navigation.

Dhruv Shah, Arjun Bhorkar, Hrishit Leen, Ilya Kostrikov, Nicholas Rhinehart, Sergey Levine

Proceedings of the Conference on Robot Learning, 2022

Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty.

Charles Packer, Nicholas Rhinehart, Rowan Thomas McAllister, Matthew A. Wright, Xin Wang, Jeff He, Sergey Levine, Joseph E. Gonzalez

Proceedings of the Conference on Robot Learning, 2022

2021

Explore and Control with Adversarial Surprise.

Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, Sergey Levine

CoRR, 2021

RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models.

Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine

CoRR, 2021

Information is Power: Intrinsic Control via Information Capture.

Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ViNG: Learning Open-World Navigation with Visual Goals.

Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models.

Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Parrot: Data-Driven Behavioral Priors for Reinforcement Learning.

Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

Conservative Safety Critics for Exploration.

Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg

Proceedings of the 9th International Conference on Learning Representations, 2021

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments.

Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

Rapid Exploration for Open-World Navigation with Latent Goal Models.

Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

First-Person Activity Forecasting from Video with Online Inverse Reinforcement Learning.

Nicholas Rhinehart, Kris M. Kitani

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Unsupervised Sequence Forecasting of 100,000 Points for Unsupervised Trajectory Forecasting.

Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart

CoRR, 2020

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

Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal

Proceedings of the 37th International Conference on Machine Learning, 2020

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

Nicholas Rhinehart, Rowan McAllister, Sergey Levine

Proceedings of the 8th International Conference on Learning Representations, 2020

Generative Hybrid Representations for Activity Forecasting With No-Regret Learning.

Jiaqi Guan, Ye Yuan, Kris M. Kitani, Nicholas Rhinehart

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting.

Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Jointly Forecasting and Controlling Behavior by Learning from High-Dimensional Data.

Nicholas Rhinehart

PhD thesis, 2019

Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information.

Mohit Sharma, Arjun Sharma, Nicholas Rhinehart, Kris M. Kitani

Proceedings of the 7th International Conference on Learning Representations, 2019

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

Nicholas Rhinehart, Rowan McAllister, Kris Kitani, Sergey Levine

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Human-Interactive Subgoal Supervision for Efficient Inverse Reinforcement Learning.

Xinlei Pan, Eshed Ohn-Bar, Nicholas Rhinehart, Yan Xu, Yilin Shen, Kris M. Kitani

CoRR, 2018

N2N learning: Network to Network Compression via Policy Gradient Reinforcement Learning.

Anubhav Ashok, Nicholas Rhinehart, Fares Beainy, Kris M. Kitani

Proceedings of the 6th International Conference on Learning Representations, 2018

r2p2: A ReparameteRized Pushforward Policy for Diverse, Precise Generative Path Forecasting.

Nicholas Rhinehart, Kris M. Kitani, Paul Vernaza

Proceedings of the Computer Vision - ECCV 2018, 2018

Learning Neural Parsers with Deterministic Differentiable Imitation Learning.

Tanmay Shankar, Nicholas Rhinehart, Katharina Muelling, Kris M. Kitani

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Predictive-State Decoders: Encoding the Future into Recurrent Networks.

Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, James Andrew Bagnell

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

First-Person Activity Forecasting with Online Inverse Reinforcement Learning.

Nicholas Rhinehart, Kris M. Kitani

Proceedings of the IEEE International Conference on Computer Vision, 2017

2016

Online Semantic Activity Forecasting with DARKO.

Nicholas Rhinehart, Kris M. Kitani

CoRR, 2016

Learning Action Maps of Large Environments via First-Person Vision.

Nicholas Rhinehart, Kris Makoto Kitani

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Visual chunking: A list prediction framework for region-based object detection.

Nicholas Rhinehart, Jiaji Zhou, Martial Hebert, J. Andrew Bagnell

Proceedings of the IEEE International Conference on Robotics and Automation, 2015