Yisong Yue

Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning L4DC 2025 InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences ICLR 2025 Population Transformer: Learning Population-level Representations of Neural Activity ICLR 2025 Visual Agentic AI for Spatial Reasoning with a Dynamic API CVPR 2025 Self-Evolving Visual Concept Library using Vision-Language Critics CVPR 2025 Find Any Part in 3D ICCV 2025 Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search ICLR 2025 Beyond Numeric Rewards: In-Context Dueling Bandits with LLM Agents ACL 2025 Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion ICML 2024 SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code ICML 2024 Online Policy Optimization in Unknown Nonlinear Systems COLT 2024 SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models NIPS 2024 CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes NIPS 2024 ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search NIPS 2024 Disentangling Linear Quadratic Control with Untrusted ML Predictions NIPS 2024 Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors NIPS 2024 Practical Bayesian Algorithm Execution via Posterior Sampling NIPS 2024 Uncertainty Calibration for Tool-Using Language Agents EMNLP 2024 Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models ICML 2024 BKinD-3D: Self-Supervised 3D Keypoint Discovery From Multi-View Videos CVPR 2023 MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior ICML 2023 Eventual Discounting Temporal Logic Counterfactual Experience Replay ICML 2023 Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach IJCAI 2023 SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems NIPS 2023 Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation ICML 2023 Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations NIPS 2023 Policy Optimization with Linear Temporal Logic Constraints NIPS 2022 Self-Supervised Keypoint Discovery in Behavioral Videos CVPR 2022 LyaNet: A Lyapunov Framework for Training Neural ODEs ICML 2022 Investigating Generalization by Controlling Normalized Margin ICML 2022 Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis CVPR 2022 Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies L4DC 2022 Safety-Aware Preference-Based Learning for Safety-Critical Control L4DC 2022 Competitive policy optimization UAI 2021 Meta-Adaptive Nonlinear Control: Theory and Algorithms NIPS 2021 DeepGEM: Generalized Expectation-Maximization for Blind Inversion NIPS 2021 Iterative Amortized Policy Optimization NIPS 2021 Deep Bayesian Quadrature Policy Optimization AAAI 2021 Minimax Model Learning AISTATS 2021 Active Learning under Label Shift AISTATS 2021 Online Robust Control of Nonlinear Systems with Large Uncertainty AISTATS 2021 Task Programming: Learning Data Efficient Behavior Representations CVPR 2021 Learning to Make Decisions via Submodular Regularization ICLR 2021 Learning by Turning: Neural Architecture Aware Optimisation ICML 2021 Learning for Safety-Critical Control with Control Barrier Functions L4DC 2020 Dueling Posterior Sampling for Preference-Based Reinforcement Learning UAI 2020 On the distance between two neural networks and the stability of learning NIPS 2020 Online Optimization with Memory and Competitive Control NIPS 2020 Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis ICML 2020 Learning Calibratable Policies using Programmatic Style-Consistency ICML 2020 A General Large Neighborhood Search Framework for Solving Integer Linear Programs NIPS 2020 Learning compositional functions via multiplicative weight updates NIPS 2020 Learning Differentiable Programs with Admissible Neural Heuristics NIPS 2020 The Power of Predictions in Online Control NIPS 2020 Robust Regression for Safe Exploration in Control L4DC 2020 Control Regularization for Reduced Variance Reinforcement Learning ICML 2019 Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design AISTATS 2019 A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes AISTATS 2019 Generating Multi-Agent Trajectories using Programmatic Weak Supervision ICLR 2019 Teaching Multiple Concepts to a Forgetful Learner NIPS 2019 Batch Policy Learning under Constraints ICML 2019 Landmark Ordinal Embedding NIPS 2019 Imitation-Projected Programmatic Reinforcement Learning NIPS 2019 Co-training for Policy Learning UAI 2019 NAOMI: Non-Autoregressive Multiresolution Sequence Imputation NIPS 2019 Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners NIPS 2018 Hierarchical Imitation and Reinforcement Learning ICML 2018 Iterative Amortized Inference ICML 2018 Stagewise Safe Bayesian Optimization with Gaussian Processes ICML 2018 A General Method for Amortizing Variational Filtering NIPS 2018 Near-Optimal Machine Teaching via Explanatory Teaching Sets AISTATS 2018 Advancements in Dueling Bandits IJCAI 2018 Teaching Categories to Human Learners With Visual Explanations CVPR 2018 Factorized Variational Autoencoders for Modeling Audience Reactions to Movies CVPR 2017 Coordinated Multi-Agent Imitation Learning ICML 2017 Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees CVPR 2016 Smooth Imitation Learning for Online Sequence Prediction ICML 2016 Generating Long-term Trajectories Using Deep Hierarchical Networks NIPS 2016 Smooth Interactive Submodular Set Cover NIPS 2015 Learning Policies for Contextual Submodular Prediction ICML 2013 Linear Submodular Bandits and their Application to Diversified Retrieval NIPS 2011 Multi-Level Structured Models for Document-Level Sentiment Classification EMNLP 2010