Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning

Nov 19, 2020
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine

* First two authors contributed equally. Project website: https://sites.google.com/view/parrot-rl 

  Access Paper or Ask Questions

Conservative Safety Critics for Exploration

Oct 27, 2020
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg

* Preprint. Under review 

  Access Paper or Ask Questions

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

Jun 26, 2020
Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal

* Camera-ready version, International Conference of Machine Learning 2020 

  Access Paper or Ask Questions

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

Mar 29, 2020
Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart

* Code will be available at https://github.com/xinshuoweng/SPCSF 

  Access Paper or Ask Questions

Sequential Forecasting of 100,000 Points

Mar 18, 2020
Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, Nicholas Rhinehart

* Code will be available at https://github.com/xinshuoweng/SPCSF 

  Access Paper or Ask Questions

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

May 07, 2019
Nicholas Rhinehart, Rowan McAllister, Kris Kitani, Sergey Levine

* Website: https://sites.google.com/view/precog 

  Access Paper or Ask Questions

Generative Hybrid Representations for Activity Forecasting with No-Regret Learning

Apr 12, 2019
Jiaqi Guan, Ye Yuan, Kris M. Kitani, Nicholas Rhinehart

* 15 pages, 4 tables, 5 figures 

  Access Paper or Ask Questions

Deep Imitative Models for Flexible Inference, Planning, and Control

Jan 31, 2019
Nicholas Rhinehart, Rowan McAllister, Sergey Levine


  Access Paper or Ask Questions

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

Sep 29, 2018
Arjun Sharma, Mohit Sharma, Nicholas Rhinehart, Kris M. Kitani


  Access Paper or Ask Questions

Learning Neural Parsers with Deterministic Differentiable Imitation Learning

Sep 19, 2018
Tanmay Shankar, Nicholas Rhinehart, Katharina Muelling, Kris M. Kitani

* Accepted to Conference on Robot Learning, CoRL 2018 

  Access Paper or Ask Questions

Human-Interactive Subgoal Supervision for Efficient Inverse Reinforcement Learning

Jun 22, 2018
Xinlei Pan, Eshed Ohn-Bar, Nicholas Rhinehart, Yan Xu, Yilin Shen, Kris M. Kitani


  Access Paper or Ask Questions

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

Dec 17, 2017
Anubhav Ashok, Nicholas Rhinehart, Fares Beainy, Kris M. Kitani


  Access Paper or Ask Questions

Predictive-State Decoders: Encoding the Future into Recurrent Networks

Sep 25, 2017
Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, J. Andrew Bagnell

* NIPS 2017 

  Access Paper or Ask Questions

First-Person Activity Forecasting with Online Inverse Reinforcement Learning

Aug 06, 2017
Nicholas Rhinehart, Kris M. Kitani

* To appear at ICCV 2017 (Oral) 

  Access Paper or Ask Questions

Learning Action Maps of Large Environments via First-Person Vision

May 05, 2016
Nicholas Rhinehart, Kris M. Kitani

* To appear at CVPR 2016 

  Access Paper or Ask Questions

Visual Chunking: A List Prediction Framework for Region-Based Object Detection

Mar 16, 2015
Nicholas Rhinehart, Jiaji Zhou, Martial Hebert, J. Andrew Bagnell

* to appear at ICRA 2015 

  Access Paper or Ask Questions