Amy Zhang
47 papers · 2018–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (13) π Interdisciplinary Bridge π Conference Polyglot (9)
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Conference Polyglot
(9)
π
Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(13)
π¬
Deep Specialist
(12)
π§¬
Topic Evolution
π
Grand Slam
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Triple Crown
ποΈ
Keyword Collector
(131)
β‘
Prolific Year
(13)
π
Conference Pioneer
π
Century Club
(47)
π₯
Unstoppable
(6)
β
The Questioner
Conferences
ICLR (18)
ICML (12)
NIPS (8)
L4DC (3)
AAAI (2)
ACL (1)
CORL (1)
RSS (1)
UAI (1)
Top co-authors
Research topics
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