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← Authors

Shixiang (Shane) Gu

14 papers · 2015–2023 · 2 conferences · across top CS/AI conferences

Achievements

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+8 more ↓ 🌍 Conference Polyglot (2) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (8)
🌍 Conference Polyglot (2) πŸƒ Academic Marathon (8) 🌈 Renaissance Researcher (7) 🌟 Keyword Trendsetter Combo (4) πŸ”₯ Unstoppable (7) πŸ’Ž Century Club (14) πŸ—ƒοΈ Keyword Collector (76) ❓ The Questioner

Conferences

NIPS (13) CORL (1)

Top co-authors

Yutaka Matsuo (3) Ofir Nachum (3) Zoubin Ghahramani (3) Scott Fujimoto (2) Richard E Turner (2) Chelsea Finn (2) Sergey Levine (2) Tatsuya Matsushima (1) Paul Yoo (1) Tadashi Kozuno (1)

Keywords

offline reinforcement learning (3) continuous control (3) deep reinforcement learning (3) hierarchical reinforcement learning (3) sample efficiency (2) instruction following (2) off-policy learning (2) sequential monte carlo (2) multi-task learning (1) sim-to-real transfer (1) multi-agent reinforcement learning (1) maximum entropy (1) variational inference (1) ensemble learning (1) imitation learning (1) nonparametric bayesian (1) zero-shot learning (1) embedding learning (1) weakly supervised learning (1) uncertainty quantification (1)

Papers

DreamSparse: Escaping from Plato’s Cave with 2D Diffusion Model Given Sparse Views NIPS 2023 For SALE: State-Action Representation Learning for Deep Reinforcement Learning NIPS 2023 Large Language Models are Zero-Shot Reasoners NIPS 2022 Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters NIPS 2022 Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning NIPS 2021 A Minimalist Approach to Offline Reinforcement Learning NIPS 2021 Weakly-Supervised Reinforcement Learning for Controllable Behavior NIPS 2020 Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real CORL 2019 Language as an Abstraction for Hierarchical Deep Reinforcement Learning NIPS 2019 SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies NIPS 2019 Data-Efficient Hierarchical Reinforcement Learning NIPS 2018 Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning NIPS 2017 Neural Adaptive Sequential Monte Carlo NIPS 2015 Particle Gibbs for Infinite Hidden Markov Models NIPS 2015