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Justin Fu
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2020 – today
- 2023
- [c17]Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust
, Shimon Whiteson, Dragomir Anguelov, Sergey Levine:
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. IROS 2023: 7553-7560 - [c16]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 - [i19]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 abs/2310.08710 (2023) - 2022
- [c15]Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, Dragomir Anguelov:
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. IROS 2022: 8652-8659 - [c14]Charlie Snell, Sherry Yang, Justin Fu, Yi Su, Sergey Levine:
Context-Aware Language Modeling for Goal-Oriented Dialogue Systems. NAACL-HLT (Findings) 2022: 2351-2366 - [c13]Siddharth Verma, Justin Fu, Sherry Yang, Sergey Levine:
CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning. NAACL-HLT 2022: 4471-4491 - [i18]Siddharth Verma, Justin Fu, Mengjiao Yang, Sergey Levine:
CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning. CoRR abs/2204.08426 (2022) - [i17]Charlie Snell, Mengjiao Yang, Justin Fu, Yi Su, Sergey Levine:
Context-Aware Language Modeling for Goal-Oriented Dialogue Systems. CoRR abs/2204.10198 (2022) - [i16]Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, Dragomir Anguelov:
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. CoRR abs/2210.09539 (2022) - [i15]Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust
, Shimon Whiteson, Dragomir Anguelov, Sergey Levine:
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. CoRR abs/2212.11419 (2022) - 2021
- [j1]Justin Fu, Andrea Tacchetti, Julien Pérolat, Yoram Bachrach:
Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning. J. Artif. Intell. Res. 71: 925-951 (2021) - [c12]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. ICLR 2021 - [c11]Justin Fu, Sergey Levine:
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation. ICLR 2021 - [c10]Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine:
Learning to Reach Goals via Iterated Supervised Learning. ICLR 2021 - [i14]Justin Fu, Sergey Levine:
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation. CoRR abs/2102.07970 (2021) - [i13]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. CoRR abs/2103.16596 (2021) - 2020
- [i12]Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine:
D4RL: Datasets for Deep Data-Driven Reinforcement Learning. CoRR abs/2004.07219 (2020) - [i11]Sergey Levine, Aviral Kumar, George Tucker, Justin Fu:
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems. CoRR abs/2005.01643 (2020)
2010 – 2019
- 2019
- [c9]Justin Fu, Anoop Korattikara, Sergey Levine, Sergio Guadarrama:
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following. ICLR (Poster) 2019 - [c8]Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine:
Diagnosing Bottlenecks in Deep Q-learning Algorithms. ICML 2019: 2021-2030 - [c7]Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, Sergey Levine:
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction. NeurIPS 2019: 11761-11771 - [c6]Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine:
When to Trust Your Model: Model-Based Policy Optimization. NeurIPS 2019: 12498-12509 - [i10]Justin Fu, Anoop Korattikara, Sergey Levine, Sergio Guadarrama:
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following. CoRR abs/1902.07742 (2019) - [i9]Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine:
Diagnosing Bottlenecks in Deep Q-learning Algorithms. CoRR abs/1902.10250 (2019) - [i8]Aviral Kumar, Justin Fu, George Tucker, Sergey Levine:
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction. CoRR abs/1906.00949 (2019) - [i7]Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine:
When to Trust Your Model: Model-Based Policy Optimization. CoRR abs/1906.08253 (2019) - [i6]Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine:
Learning To Reach Goals Without Reinforcement Learning. CoRR abs/1912.06088 (2019) - 2018
- [c5]Justin Fu, Katie Luo, Sergey Levine:
Learning Robust Rewards with Adverserial Inverse Reinforcement Learning. ICLR (Poster) 2018 - [c4]Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine:
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. NeurIPS 2018: 8547-8556 - [i5]Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine:
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. CoRR abs/1805.11686 (2018) - 2017
- [c3]Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine:
Generalizing Skills with Semi-Supervised Reinforcement Learning. ICLR (Poster) 2017 - [c2]Justin Fu, John D. Co-Reyes, Sergey Levine:
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning. NIPS 2017: 2577-2587 - [i4]Justin Fu, John D. Co-Reyes, Sergey Levine:
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning. CoRR abs/1703.01260 (2017) - [i3]Justin Fu, Katie Luo, Sergey Levine:
Learning Robust Rewards with Adversarial Inverse Reinforcement Learning. CoRR abs/1710.11248 (2017) - 2016
- [c1]Justin Fu, Sergey Levine, Pieter Abbeel:
One-shot learning of manipulation skills with online dynamics adaptation and neural network priors. IROS 2016: 4019-4026 - [i2]Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine:
Generalizing Skills with Semi-Supervised Reinforcement Learning. CoRR abs/1612.00429 (2016) - 2015
- [i1]Justin Fu, Sergey Levine, Pieter Abbeel:
One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors. CoRR abs/1509.06841 (2015)
Coauthor Index
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