← Authors

Amy Zhang

47 papers · 2018–2025 · 9 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) πŸ”¬ Deep Specialist (12) 🧬 Topic Evolution πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (131) ⚑ Prolific Year (13) πŸš€ Conference Pioneer πŸ’Ž Century Club (47) πŸ”₯ Unstoppable (6) ❓ The Questioner

Conferences

ICLR (18) ICML (12) NIPS (8) L4DC (3) AAAI (2) ACL (1) CORL (1) RSS (1) UAI (1)

Top co-authors

Shagun Sodhani (9) Joelle Pineau (8) Scott Niekum (6) Harshit Sikchi (6) Sergey Levine (5) Peter Stone (4) Franziska Meier (3) Doina Precup (3) Qinqing Zheng (3) Pascal Vincent (3)

Research topics

Optimization & Theory (1)

Keywords

reinforcement learning (6) representation learning (5) offline reinforcement learning (4) policy learning (4) state abstraction (3) sample efficiency (3) goal-conditioned reinforcement learning (3) multi-task learning (2) policy gradient (2) entropy regularization (2) sparse reward (2) causal inference (2) policy optimization (2) imitation learning (1) lottery ticket hypothesis (1) deep reinforcement learning (1) robust optimization (1) transformer architecture (1) text classification (1) transfer learning (1)

Papers

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