← Authors

Yisong Yue

82 papers · 2010–2025 · 13 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (15) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (13) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (31) 🌟 Keyword Trendsetter Combo (6) 🏠 Conference Loyalist (27) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ‘₯ Mega-Team (23) 🧬 Topic Evolution πŸ”¬ Deep Specialist (11) πŸ† Keyword Champion (2) πŸš€ Conference Pioneer πŸ’Ž Century Club (82) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (92) πŸ”₯ Unstoppable (11) ⚑ Prolific Year (11)

Conferences

NIPS (27) ICML (19) CVPR (9) AISTATS (6) ICLR (5) L4DC (5) UAI (3) EMNLP (2) IJCAI (2) AAAI (1) ACL (1) COLT (1) ICCV (1)

Top co-authors

Yuxin Chen (9) Pietro Perona (8) Hoang Le (6) Ziniu Hu (6) Jennifer J. Sun (6) Jialin Song (5) Soon-Jo Chung (5) Eric Zhan (5) Swarat Chaudhuri (5) Adam Wierman (5)

Research topics

Models (1) Education (1)

Keywords

reinforcement learning (8) imitation learning (6) online learning (5) bayesian optimization (4) policy learning (4) submodular optimization (4) program synthesis (4) combinatorial optimization (4) gaussian process (4) machine teaching (3) self-supervised learning (3) concept learning (3) sequential decision making (3) regret bound (3) policy optimization (3) continuous control (3) trajectory prediction (3) posterior sampling (3) off-policy learning (3) control barrier function (3)

Papers

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