Justin Fu - RankMe

40 papers A* 8A 3Journal 21Unranked 7

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Improving Agent Behaviors with RL Fine-Tuning for Autonomous Driving. ECCV (25) Zhenghao Peng, Wenjie Luo, Yiren Lu, Tianyi Shen, Cole Gulino, Ari Seff, Justin Fu
2024	J	`jnl`	Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving. CoRR Zhenghao Peng, Wenjie Luo, Yiren Lu, Tianyi Shen, Cole Gulino, Ari Seff, Justin Fu
2023	A	`conf`	Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. IROS Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine
2023	A*	`conf`	Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. NeurIPS 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
2023	J	`jnl`	Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. CoRR 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
2022	—	`conf`	CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning. NAACL-HLT Siddharth Verma, Justin Fu, Sherry Yang, Sergey Levine
2022	J	`jnl`	CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning. CoRR Siddharth Verma, Justin Fu, Mengjiao Yang, Sergey Levine
2022	—	`conf`	Context-Aware Language Modeling for Goal-Oriented Dialogue Systems. NAACL-HLT (Findings) Charlie Snell, Sherry Yang, Justin Fu, Yi Su, Sergey Levine
2022	J	`jnl`	Context-Aware Language Modeling for Goal-Oriented Dialogue Systems. CoRR Charlie Snell, Mengjiao Yang, Justin Fu, Yi Su, Sergey Levine
2022	A	`conf`	Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. IROS 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
2022	J	`jnl`	Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. CoRR 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
2022	J	`jnl`	Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. CoRR Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine
2021	A*	`conf`	Benchmarks for Deep Off-Policy Evaluation. ICLR 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
2021	J	`jnl`	Benchmarks for Deep Off-Policy Evaluation. CoRR 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
2021	J	`jnl`	Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning. J. Artif. Intell. Res. Justin Fu, Andrea Tacchetti, Julien Pérolat, Yoram Bachrach
2021	A*	`conf`	Learning to Reach Goals via Iterated Supervised Learning. ICLR Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine
2021	—	`—`	Offline Learning for Scalable Decision Making Justin Fu
2021	A*	`conf`	Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation. ICLR Justin Fu, Sergey Levine
2021	J	`jnl`	Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation. CoRR Justin Fu, Sergey Levine
2020	J	`jnl`	D4RL: Datasets for Deep Data-Driven Reinforcement Learning. CoRR Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine
2020	J	`jnl`	Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems. CoRR Sergey Levine, Aviral Kumar, George Tucker, Justin Fu
2019	A*	`conf`	Diagnosing Bottlenecks in Deep Q-learning Algorithms. ICML Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine
2019	J	`jnl`	Diagnosing Bottlenecks in Deep Q-learning Algorithms. CoRR Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine
2019	—	`conf`	From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following. ICLR (Poster) Justin Fu, Anoop Korattikara, Sergey Levine, Sergio Guadarrama
2019	J	`jnl`	From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following. CoRR Justin Fu, Anoop Korattikara, Sergey Levine, Sergio Guadarrama
2019	J	`jnl`	Learning To Reach Goals Without Reinforcement Learning. CoRR Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine
2019	A*	`conf`	Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction. NeurIPS Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, Sergey Levine
2019	J	`jnl`	Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction. CoRR Aviral Kumar, Justin Fu, George Tucker, Sergey Levine
2019	A*	`conf`	When to Trust Your Model: Model-Based Policy Optimization. NeurIPS Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine
2019	J	`jnl`	When to Trust Your Model: Model-Based Policy Optimization. CoRR Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine
2018	—	`conf`	Learning Robust Rewards with Adverserial Inverse Reinforcement Learning. ICLR (Poster) Justin Fu, Katie Luo, Sergey Levine
2018	A*	`conf`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. NeurIPS Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2018	J	`jnl`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. CoRR Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2017	—	`conf`	EX2: Exploration with Exemplar Models for Deep Reinforcement Learning. NIPS Justin Fu, John D. Co-Reyes, Sergey Levine
2017	J	`jnl`	EX2: Exploration with Exemplar Models for Deep Reinforcement Learning. CoRR Justin Fu, John D. Co-Reyes, Sergey Levine
2017	—	`conf`	Generalizing Skills with Semi-Supervised Reinforcement Learning. ICLR (Poster) Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Learning Robust Rewards with Adversarial Inverse Reinforcement Learning. CoRR Justin Fu, Katie Luo, Sergey Levine
2016	J	`jnl`	Generalizing Skills with Semi-Supervised Reinforcement Learning. CoRR Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine
2016	A	`conf`	One-shot learning of manipulation skills with online dynamics adaptation and neural network priors. IROS Justin Fu, Sergey Levine, Pieter Abbeel
2015	J	`jnl`	One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors. CoRR Justin Fu, Sergey Levine, Pieter Abbeel