Shixiang Gu - RankMe

54 papers A* 12Misc 1Journal 25Unranked 15

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Construction of a High-Resolution Waterlogging Disaster Monitoring Framework Based on the APSIM Model: A Case Study of Jingzhou and Bengbu. Remote. Sens. Jian Zhang, Bin Pan, Wenxuan Shi, Yu Zhang, Shixiang Gu, Jinming Chen, Quanbin Xia
2024	J	`jnl`	Optimal Mapping of Soil Erodibility in a Plateau Lake Watershed: Empirical Models Empowered by Machine Learning. Remote. Sens. Jiaxue Wang, Yujiao Wei, Zheng Sun, Shixiang Gu, Shihan Bai, Jinming Chen, Jing Chen, Yongsheng Hong, Yiyun Chen
2023	A*	`conf`	For SALE: State-Action Representation Learning for Deep Reinforcement Learning. NeurIPS Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Gu, Doina Precup, David Meger
2023	A*	`conf`	Large Language Models Can Self-Improve. EMNLP Jiaxin Huang, Shixiang Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
2022	J	`jnl`	Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning. CoRR Seyed Kamyar Seyed Ghasemipour, Daniel Freeman, Byron David, Shixiang Gu, Satoshi Kataoka, Igor Mordatch
2021	A*	`conf`	Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization. ICLR Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
2020	J	`jnl`	Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization. CoRR Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
2020	A*	`conf`	Dynamics-Aware Unsupervised Discovery of Skills. ICLR Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman
2020	—	`conf`	Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning. Robotics: Science and Systems Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu
2020	J	`jnl`	Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning. CoRR Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu
2020	—	`conf`	Human-centric dialog training via offline reinforcement learning. EMNLP (1) Natasha Jaques, Judy Hanwen Shen, Asma Ghandeharioun, Craig Ferguson, Àgata Lapedriza, Noah Jones, Shixiang Gu, Rosalind W. Picard
2020	J	`jnl`	Weakly-Supervised Reinforcement Learning for Controllable Behavior. CoRR Lisa Lee, Benjamin Eysenbach, Ruslan Salakhutdinov, Shixiang Gu, Chelsea Finn
2019	Misc	`conf`	A Divergence Minimization Perspective on Imitation Learning Methods. CoRL Seyed Kamyar Seyed Ghasemipour, Richard S. Zemel, Shixiang Gu
2019	J	`jnl`	A Divergence Minimization Perspective on Imitation Learning Methods. CoRR Seyed Kamyar Seyed Ghasemipour, Richard S. Zemel, Shixiang Gu
2019	—	`conf`	Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives. ICLR (Poster) George Tucker, Dieterich Lawson, Shixiang Gu, Chris J. Maddison
2019	J	`jnl`	Dynamics-Aware Unsupervised Discovery of Skills. CoRR Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman
2019	A*	`conf`	Language as an Abstraction for Hierarchical Deep Reinforcement Learning. NeurIPS Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn
2019	J	`jnl`	Language as an Abstraction for Hierarchical Deep Reinforcement Learning. CoRR Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn
2019	J	`jnl`	Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real. CoRR Ofir Nachum, Michael Ahn, Hugo Ponte, Shixiang Gu, Vikash Kumar
2019	—	`conf`	Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. ICLR (Poster) Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2019	A*	`conf`	SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies. NeurIPS Seyed Kamyar Seyed Ghasemipour, Shixiang Gu, Richard S. Zemel
2019	—	`—`	Sample-efficient deep reinforcement learning for continuous control. Shixiang Gu
2019	J	`jnl`	Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog. CoRR Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Craig Ferguson, Àgata Lapedriza, Noah Jones, Shixiang Gu, Rosalind W. Picard
2019	J	`jnl`	Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? CoRR Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine
2018	A*	`conf`	Data-Efficient Hierarchical Reinforcement Learning. NeurIPS Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	J	`jnl`	Data-Efficient Hierarchical Reinforcement Learning. CoRR Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	J	`jnl`	Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives. CoRR George Tucker, Dieterich Lawson, Shixiang Gu, Chris J. Maddison
2018	—	`conf`	Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. ICLR (Poster) Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine
2018	J	`jnl`	Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. CoRR Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	—	`conf`	Temporal Difference Models: Model-Free Deep RL for Model-Based Control. ICLR (Poster) Vitchyr Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine
2018	J	`jnl`	Temporal Difference Models: Model-Free Deep RL for Model-Based Control. CoRR Vitchyr Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine
2018	—	`conf`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. ICLR (Workshop) George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	A*	`conf`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. ICML George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2018	J	`jnl`	The Mirage of Action-Dependent Baselines in Reinforcement Learning. CoRR George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E. Turner, Zoubin Ghahramani, Sergey Levine
2017	—	`conf`	Categorical Reparameterization with Gumbel-Softmax. ICLR (Poster) Eric Jang, Shixiang Gu, Ben Poole
2017	A*	`conf`	Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates. ICRA Shixiang Gu, Ethan Holly, Timothy P. Lillicrap, Sergey Levine
2017	—	`conf`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. NIPS Shixiang Gu, Tim Lillicrap, Richard E. Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine
2017	J	`jnl`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. CoRR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Bernhard Schölkopf, Sergey Levine
2017	J	`jnl`	Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. CoRR Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine
2017	—	`conf`	Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic. ICLR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
2017	A*	`conf`	Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control. ICML Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, José Miguel Hernández-Lobato, Richard E. Turner, Douglas Eck
2017	—	`conf`	Tuning Recurrent Neural Networks with Reinforcement Learning. ICLR (Workshop) Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck
2016	J	`jnl`	Categorical Reparameterization with Gumbel-Softmax. CoRR Eric Jang, Shixiang Gu, Ben Poole
2016	A*	`conf`	Continuous Deep Q-Learning with Model-based Acceleration. ICML Shixiang Gu, Timothy P. Lillicrap, Ilya Sutskever, Sergey Levine
2016	J	`jnl`	Continuous Deep Q-Learning with Model-based Acceleration. CoRR Shixiang Gu, Timothy P. Lillicrap, Ilya Sutskever, Sergey Levine
2016	J	`jnl`	Deep Reinforcement Learning for Robotic Manipulation. CoRR Shixiang Gu, Ethan Holly, Timothy P. Lillicrap, Sergey Levine
2016	A*	`conf`	MuProp: Unbiased Backpropagation for Stochastic Neural Networks. ICLR (Poster) Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih
2016	J	`jnl`	Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic. CoRR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
2016	J	`jnl`	Tuning Recurrent Neural Networks with Reinforcement Learning. CoRR Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck
2015	—	`conf`	Neural Adaptive Sequential Monte Carlo. NIPS Shixiang Gu, Zoubin Ghahramani, Richard E. Turner
2015	J	`jnl`	Neural Adaptive Sequential Monte Carlo. CoRR Shixiang Gu, Zoubin Ghahramani, Richard E. Turner
2015	—	`conf`	Particle Gibbs for Infinite Hidden Markov Models. NIPS Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani
2015	—	`conf`	Towards Deep Neural Network Architectures Robust to Adversarial Examples. ICLR (Workshop) Shixiang Gu, Luca Rigazio
2012	—	`conf`	Realtime HDR (High Dynamic Range) video for eyetap wearable computers, FPGA-based seeing aids, and glasseyes (EyeTaps). CCECE Steve Mann, Raymond Chun Hing Lo, Kalin Ovtcharov, Shixiang Gu, David Dai, Calvin Ngan, Tao Ai