Amy Zhang

Enhancing Accuracy of Uncertainty Estimation in Appearance-based Gaze Tracking with Probabilistic Evaluation and Calibration CVPR 2026 An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning ICLR 2025 CREStE: Scalable Mapless Navigation with Internet Scale Priors and Counterfactual Guidance RSS 2025 EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation ICLR 2025 Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory ICLR 2025 MaestroMotif: Skill Design from Artificial Intelligence Feedback ICLR 2025 Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning ICLR 2025 Proto Successor Measure: Representing the Behavior Space of an RL Agent ICML 2025 StitchLLM: Serving LLMs, One Block at a Time ACL 2025 Towards General-Purpose Model-Free Reinforcement Learning ICLR 2025 A Dual Approach to Imitation Learning from Observations with Offline Datasets CoRL 2024 AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers NeurIPS 2024 An investigation of time reversal symmetry in reinforcement learning L4DC 2024 Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning NeurIPS 2024 Dual RL: Unification and New Methods for Reinforcement and Imitation Learning ICLR 2024 Efficient Reinforcement Learning by Discovering Neural Pathways NeurIPS 2024 Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks ICLR 2024 Motif: Intrinsic Motivation from Artificial Intelligence Feedback ICLR 2024 Score Models for Offline Goal-Conditioned Reinforcement Learning ICLR 2024 SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions NeurIPS 2024 Towards Robust Offline Reinforcement Learning under Diverse Data Corruption ICLR 2024 When should we prefer Decision Transformers for Offline Reinforcement Learning? ICLR 2024 Zero-Shot Reinforcement Learning via Function Encoders ICML 2024 Accelerating Exploration with Unlabeled Prior Data NeurIPS 2023 BC-IRL: Learning Generalizable Reward Functions from Demonstrations ICLR 2023 f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences NeurIPS 2023 Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement ICLR 2023 Latent State Marginalization as a Low-cost Approach for Improving Exploration ICLR 2023 LIV: Language-Image Representations and Rewards for Robotic Control ICML 2023 Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning ICML 2023 Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability NeurIPS 2023 VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training ICLR 2023 Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning ICML 2022 Block Contextual MDPs for Continual Learning L4DC 2022 Denoised MDPs: Learning World Models Better Than the World Itself ICML 2022 Online Decision Transformer ICML 2022 Predicting the Influence of Fake and Real News Spreaders (Student Abstract) AAAI 2022 Robust Policy Learning over Multiple Uncertainty Sets ICML 2022 Improving Sample Efficiency in Model-Free Reinforcement Learning from Images AAAI 2021 Learning Invariant Representations for Reinforcement Learning without Reconstruction ICLR 2021 Learning Robust State Abstractions for Hidden-Parameter Block MDPs ICLR 2021 Multi-Task Reinforcement Learning with Context-based Representations ICML 2021 Out-of-Distribution Generalization via Risk Extrapolation (REx) ICML 2021 Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability NeurIPS 2021 Invariant Causal Prediction for Block MDPs ICML 2020 Plan2Vec: Unsupervised Representation Learning by Latent Plans L4DC 2020 Stable Policy Optimization via Off-Policy Divergence Regularization UAI 2020 Composable Planning with Attributes ICML 2018