Gu, Shixiang

30 publications

NeurIPS 2023 DreamSparse: Escaping from Plato’s Cave with 2D Diffusion Model Given Sparse Views Paul Yoo, Jiaxian Guo, Yutaka Matsuo, Shixiang Gu

NeurIPS 2023 For SALE: State-Action Representation Learning for Deep Reinforcement Learning Scott Fujimoto, Wei-Di Chang, Edward Smith, Shixiang Gu, Doina Precup, David Meger

NeurIPS 2022 Large Language Models Are Zero-Shot Reasoners Takeshi Kojima, Shixiang Gu, Machel Reid, Yutaka Matsuo, Yusuke Iwasawa

NeurIPS 2022 Why so Pessimistic? Estimating Uncertainties for Offline RL Through Ensembles, and Why Their Independence Matters Kamyar Ghasemipour, Shixiang Gu, Ofir Nachum

NeurIPS 2021 A Minimalist Approach to Offline Reinforcement Learning Scott Fujimoto, Shixiang Gu

NeurIPS 2021 Co-Adaptation of Algorithmic and Implementational Innovations in Inference-Based Deep Reinforcement Learning Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Gu

ICLR 2021 Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu

ICLR 2020 Dynamics-Aware Unsupervised Skill Discovery Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman

ICLR 2020 Way Off-Policy Batch Deep Reinforcement Learning of Human Preferences in Dialog Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Gu, Rosalind Picard

NeurIPS 2020 Weakly-Supervised Reinforcement Learning for Controllable Behavior Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov, Shixiang Gu, Chelsea Finn

CoRL 2019 A Divergence Minimization Perspective on Imitation Learning Methods Seyed Kamyar Seyed Ghasemipour, Richard Zemel, Shixiang Gu

ICLR 2019 Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives George Tucker, Dieterich Lawson, Shixiang Gu, Chris J. Maddison

NeurIPS 2019 Language as an Abstraction for Hierarchical Deep Reinforcement Learning YiDing Jiang, Shixiang Gu, Kevin P. Murphy, Chelsea Finn

CoRL 2019 Multi-Agent Manipulation via Locomotion Using Hierarchical Sim2Real Ofir Nachum, Michael Ahn, Hugo Ponte, Shixiang Gu, Vikash Kumar

ICLR 2019 Near-Optimal Representation Learning for Hierarchical Reinforcement Learning Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine

NeurIPS 2019 SMILe: Scalable Meta Inverse Reinforcement Learning Through Context-Conditional Policies Seyed Kamyar Seyed Ghasemipour, Shixiang Gu, Richard Zemel

NeurIPS 2018 Data-Efficient Hierarchical Reinforcement Learning Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine

ICLR 2018 Leave No Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine

ICLR 2018 Temporal Difference Models: Model-Free Deep RL for Model-Based Control Vitchyr Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine

ICML 2018 The Mirage of Action-Dependent Baselines in Reinforcement Learning George Tucker, Surya Bhupatiraju, Shixiang Gu, Richard Turner, Zoubin Ghahramani, Sergey Levine

ICLR 2017 Categorical Reparameterization with Gumbel-SoftMax Eric Jang, Shixiang Gu, Ben Poole

NeurIPS 2017 Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning Shixiang Gu, Timothy Lillicrap, Richard E Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine

ICLR 2017 Q-Prop: Sample-Efficient Policy Gradient with an Off-Policy Critic Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine

ICML 2017 Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-Control Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, José Miguel Hernández-Lobato, Richard E. Turner, Douglas Eck

ICLR 2017 Tuning Recurrent Neural Networks with Reinforcement Learning Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck

ICML 2016 Continuous Deep Q-Learning with Model-Based Acceleration Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine

ICLR 2016 MuProp: Unbiased Backpropagation for Stochastic Neural Networks Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih

NeurIPS 2015 Neural Adaptive Sequential Monte Carlo Shixiang Gu, Zoubin Ghahramani, Richard E Turner

NeurIPS 2015 Particle Gibbs for Infinite Hidden Markov Models Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani

ICLR 2015 Towards Deep Neural Network Architectures Robust to Adversarial Examples Shixiang Gu, Luca Rigazio