Yue, Yisong

116 publications

NeurIPS 2025 CLEVER: A Curated Benchmark for Formally Verified Code Generation Amitayush Thakur, Jasper Lee, George Tsoukalas, Meghana Sistla, Matthew Zhao, Stefan Zetzsche, Greg Durrett, Yisong Yue, Swarat Chaudhuri

NeurIPS 2025 Conformal Risk Training: End-to-End Optimization of Conformal Risk Control Christopher Yeh, Nicolas Christianson, Adam Wierman, Yisong Yue

NeurIPS 2025 DISC: Dynamic Decomposition Improves LLM Inference Scaling Jonathan Light, Wei Cheng, Benjamin Riviere, Yue Wu, Masafumi Oyamada, Mengdi Wang, Yisong Yue, Santiago Paternain, Haifeng Chen

NeurIPS 2025 EnCompass: Enhancing Agent Programming with Search over Program Execution Paths Zhening Li, Armando Solar-Lezama, Yisong Yue, Stephan Zheng

TMLR 2025 End-to-End Conformal Calibration for Optimization Under Uncertainty Christopher Yeh, Nicolas Christianson, Alan Wu, Adam Wierman, Yisong Yue

TMLR 2025 Ensemble Kalman Diffusion Guidance: A Derivative-Free Method for Inverse Problems Hongkai Zheng, Wenda Chu, Austin Wang, Nikola Borislavov Kovachki, Ricardo Baptista, Yisong Yue

ICLRW 2025 Ensemble Kalman Sampling and Diffusion Prior in Tandem: A Split Gibbs Framework Austin Wang, Hongkai Zheng, Zihui Wu, Ricardo Baptista, Daniel Zhengyu Huang, Yisong Yue

ICCV 2025 Find Any Part in 3D Ziqi Ma, Yisong Yue, Georgia Gkioxari

ICLR 2025 InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences Hongkai Zheng, Wenda Chu, Bingliang Zhang, Zihui Wu, Austin Wang, Berthy Feng, Caifeng Zou, Yu Sun, Nikola Borislavov Kovachki, Zachary E Ross, Katherine Bouman, Yisong Yue

NeurIPS 2025 Kuramoto Orientation Diffusion Models Yue Song, T. Anderson Keller, Sevan Brodjian, Takeru Miyato, Yisong Yue, Pietro Perona, Max Welling

L4DC 2025 Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning Fengze Xie, Sizhe Wei, Yue Song, Yisong Yue, Lu Gan

ICLR 2025 Population Transformer: Learning Population-Level Representations of Neural Activity Geeling Chau, Christopher Wang, Sabera J Talukder, Vighnesh Subramaniam, Saraswati Soedarmadji, Yisong Yue, Boris Katz, Andrei Barbu

TMLR 2025 Preferential Multi-Objective Bayesian Optimization Raul Astudillo, Kejun Li, Maegan Tucker, Chu Xin Cheng, Aaron Ames, Yisong Yue

CVPR 2025 Self-Evolving Visual Concept Library Using Vision-Language Critics Atharva Sehgal, Patrick Yuan, Ziniu Hu, Yisong Yue, Jennifer J. Sun, Swarat Chaudhuri

NeurIPS 2025 Split Gibbs Discrete Diffusion Posterior Sampling Wenda Chu, Zihui Wu, Yifan Chen, Yang Song, Yisong Yue

NeurIPS 2025 Steering Generative Models with Experimental Data for Protein Fitness Optimization Jason Yang, Wenda Chu, Daniel Khalil, Raul Astudillo, Bruce James Wittmann, Frances H. Arnold, Yisong Yue

ICLRW 2025 Steering Generative Models with Experimental Data for Protein Fitness Optimization Jason Yang, Wenda Chu, Daniel Khalil, Raul Astudillo, Bruce James Wittmann, Frances H. Arnold, Yisong Yue

ICLR 2025 Strategist: Self-Improvement of LLM Decision Making via Bi-Level Tree Search Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu

ICLRW 2025 Substrate-Aware Zero-Shot Predictors for Non-Native Enzyme Activities Francesca-Zhoufan Li, Lukas Alexander Radtke, Kadina E Johnston, Cheng-Hao Liu, Yisong Yue, Frances H. Arnold

CVPR 2025 Visual Agentic AI for Spatial Reasoning with a Dynamic API Damiano Marsili, Rohun Agrawal, Yisong Yue, Georgia Gkioxari

NeurIPS 2024 CARE: A Benchmark Suite for the Classification and Retrieval of Enzymes Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Anima Anandkumar, Frances H. Arnold, Yisong Yue

NeurIPS 2024 Disentangling Linear Quadratic Control with Untrusted ML Predictions Tongxin Li, Hao Liu, Yisong Yue

TMLR 2024 Distributionally Robust Policy Evaluation Under General Covariate Shift in Contextual Bandits Yihong Guo, Hao Liu, Yisong Yue, Anqi Liu

ICML 2024 Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models Francesca-Zhoufan Li, Ava P Amini, Yisong Yue, Kevin K Yang, Alex Xijie Lu

COLT 2024 Online Policy Optimization in Unknown Nonlinear Systems Yiheng Lin, James A. Preiss, Fengze Xie, Emile Anand, Soon-Jo Chung, Yisong Yue, Adam Wierman

NeurIPSW 2024 PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Jonathan Light, Sixue Xing, Yuanzhe Liu, Weiqin Chen, Min Cai, Xiusi Chen, Guanzhi Wang, Wei Cheng, Yisong Yue, Ziniu Hu

ICMLW 2024 Population Transformer: Learning Population-Level Representations of Intracranial Activity Geeling Chau, Christopher Wang, Sabera J Talukder, Vighnesh Subramaniam, Saraswati Soedarmadji, Yisong Yue, Boris Katz, Andrei Barbu

NeurIPSW 2024 Population Transformer: Learning Population-Level Representations of Intracranial Activity Geeling Chau, Christopher Wang, Sabera J Talukder, Vighnesh Subramaniam, Saraswati Soedarmadji, Yisong Yue, Boris Katz, Andrei Barbu

NeurIPS 2024 Practical Bayesian Algorithm Execution via Posterior Sampling Chu Xin Cheng, Raul Astudillo, Thomas Desautels, Yisong Yue

NeurIPSW 2024 Practical Bayesian Algorithm Execution via Posterior Sampling Chu Xin Cheng, Raul Astudillo, Thomas Desautels, Yisong Yue

NeurIPS 2024 Principled Probabilistic Imaging Using Diffusion Models as Plug-and-Play Priors Zihui Wu, Yu Sun, Yifan Chen, Bingliang Zhang, Yisong Yue, Katherine L. Bouman

NeurIPS 2024 REST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search Dan Zhang, Sining Zhoubian, Ziniu Hu, Yisong Yue, Yuxiao Dong, Jie Tang

NeurIPSW 2024 Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving Ziyu Ye, Jiacheng Chen, Jonathan Light, Yifei Wang, Jiankai Sun, Mac Schwager, Philip Torr, Guohao Li, Yuxin Chen, Kaiyu Yang, Yisong Yue, Ziniu Hu

ICML 2024 SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code Ziniu Hu, Ahmet Iscen, Aashi Jain, Thomas Kipf, Yisong Yue, David A Ross, Cordelia Schmid, Alireza Fathi

NeurIPS 2024 SciInstruct: A Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models Dan Zhang, Ziniu Hu, Sining Zhoubian, Zhengxiao Du, Kaiyu Yang, Zihan Wang, Yisong Yue, Yuxiao Dong, Jie Tang

ICMLW 2024 Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller Min Cai, Yuchen Zhang, Shichang Zhang, Fan Yin, Difan Zou, Yisong Yue, Ziniu Hu

ICMLW 2024 Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller Min Cai, Yuchen Zhang, Shichang Zhang, Fan Yin, Difan Zou, Yisong Yue, Ziniu Hu

ICMLW 2024 Strategist: Learning Strategic Skills by LLMs via Bi-Level Tree Search Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu

ICML 2024 Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue

TMLR 2024 TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis Sabera J Talukder, Yisong Yue, Georgia Gkioxari

CVPR 2023 BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos Jennifer J. Sun, Lili Karashchuk, Amil Dravid, Serim Ryou, Sonia Fereidooni, John C. Tuthill, Aggelos Katsaggelos, Bingni W. Brunton, Georgia Gkioxari, Ann Kennedy, Yisong Yue, Pietro Perona

ICML 2023 Eventual Discounting Temporal Logic Counterfactual Experience Replay Cameron Voloshin, Abhinav Verma, Yisong Yue

IJCAI 2023 Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu, Junchi Yan

NeurIPSW 2023 Learning Expert-Interpretable Programs for Myocardial Infarction Localization Joshua Alan Flashner, Jennifer J. Sun, David Ouyang, Yisong Yue

ICML 2023 Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation Fengxue Zhang, Jialin Song, James C Bowden, Alexander Ladd, Yisong Yue, Thomas Desautels, Yuxin Chen

ICML 2023 MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior Jennifer J. Sun, Markus Marks, Andrew Wesley Ulmer, Dipam Chakraborty, Brian Geuther, Edward Hayes, Heng Jia, Vivek Kumar, Sebastian Oleszko, Zachary Partridge, Milan Peelman, Alice Robie, Catherine E Schretter, Keith Sheppard, Chao Sun, Param Uttarwar, Julian Morgan Wagner, Erik Werner, Joseph Parker, Pietro Perona, Yisong Yue, Kristin Branson, Ann Kennedy

NeurIPS 2023 Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations Yiheng Lin, James A. Preiss, Emile Anand, Yingying Li, Yisong Yue, Adam Wierman

ICMLW 2023 Preferential Multi-Attribute Bayesian Optimization with Application to Exoskeleton Personalization Raul Astudillo, Kejun Li, Maegan Tucker, Chu Xin Cheng, Aaron Ames, Yisong Yue

NeurIPS 2023 SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems Christopher Yeh, Victor Li, Rajeev Datta, Julio Arroyo, Nicolas Christianson, Chi Zhang, Yize Chen, Mohammad Mehdi Hosseini, Azarang Golmohammadi, Yuanyuan Shi, Yisong Yue, Adam Wierman

CVPR 2022 Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis Albert Tseng, Jennifer J. Sun, Yisong Yue

NeurIPSW 2022 Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings Sabera J Talukder, Jennifer J. Sun, Matthew K Leonard, Bingni W Brunton, Yisong Yue

ICML 2022 Investigating Generalization by Controlling Normalized Margin Alexander R Farhang, Jeremy D Bernstein, Kushal Tirumala, Yang Liu, Yisong Yue

ICML 2022 LyaNet: A Lyapunov Framework for Training Neural ODEs Ivan Dario Jimenez Rodriguez, Aaron Ames, Yisong Yue

L4DC 2022 Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue, Aaron D. Ames

NeurIPSW 2022 Neurosymbolic Programming for Science Jennifer J. Sun, Megan Tjandrasuwita, Atharva Sehgal, Armando Solar-Lezama, Swarat Chaudhuri, Yisong Yue, Omar Costilla Reyes

NeurIPS 2022 Policy Optimization with Linear Temporal Logic Constraints Cameron Voloshin, Hoang Le, Swarat Chaudhuri, Yisong Yue

L4DC 2022 Safety-Aware Preference-Based Learning for Safety-Critical Control Ryan Cosner, Maegan Tucker, Andrew Taylor, Kejun Li, Tamas Molnar, Wyatt Ubelacker, Anil Alan, Gabor Orosz, Yisong Yue, Aaron Ames

CVPR 2022 Self-Supervised Keypoint Discovery in Behavioral Videos Jennifer J. Sun, Serim Ryou, Roni H. Goldshmid, Brandon Weissbourd, John O. Dabiri, David J. Anderson, Ann Kennedy, Yisong Yue, Pietro Perona

TMLR 2022 Unsupervised Learning of Neurosymbolic Encoders Eric Zhan, Jennifer J. Sun, Ann Kennedy, Yisong Yue, Swarat Chaudhuri

AISTATS 2021 Active Learning Under Label Shift Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue

AISTATS 2021 Minimax Model Learning Cameron Voloshin, Nan Jiang, Yisong Yue

AISTATS 2021 Online Robust Control of Nonlinear Systems with Large Uncertainty Dimitar Ho, Hoang Le, John Doyle, Yisong Yue

UAI 2021 Competitive Policy Optimization Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar

AAAI 2021 Deep Bayesian Quadrature Policy Optimization Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue

NeurIPS 2021 DeepGEM: Generalized Expectation-Maximization for Blind Inversion Angela Gao, Jorge Castellanos, Yisong Yue, Zachary Ross, Katherine Bouman

NeurIPS 2021 Iterative Amortized Policy Optimization Joseph Marino, Alexandre Piche, Alessandro Davide Ialongo, Yisong Yue

ICML 2021 Learning by Turning: Neural Architecture Aware Optimisation Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue

ICLR 2021 Learning to Make Decisions via Submodular Regularization Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen

NeurIPS 2021 Meta-Adaptive Nonlinear Control: Theory and Algorithms Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue

CVPR 2021 Task Programming: Learning Data Efficient Behavior Representations Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Yue, Pietro Perona

NeurIPS 2020 A General Large Neighborhood Search Framework for Solving Integer Linear Programs Jialin Song, Ravi Lanka, Yisong Yue, Bistra Dilkina

UAI 2020 Dueling Posterior Sampling for Preference-Based Reinforcement Learning Ellen Novoseller, Yibing Wei, Yanan Sui, Yisong Yue, Joel Burdick

ICML 2020 Learning Calibratable Policies Using Programmatic Style-Consistency Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht

NeurIPS 2020 Learning Compositional Functions via Multiplicative Weight Updates Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue

NeurIPS 2020 Learning Differentiable Programs with Admissible Neural Heuristics Ameesh Shah, Eric Zhan, Jennifer Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri

L4DC 2020 Learning for Safety-Critical Control with Control Barrier Functions Andrew Taylor, Andrew Singletary, Yisong Yue, Aaron Ames

ICML 2020 Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis Jung Yeon Park, Kenneth Carr, Stephan Zheng, Yisong Yue, Rose Yu

NeurIPSW 2020 On the Benefits of Early Fusion in Multimodal Representation Learning George Barnum, Sabera J Talukder, Yisong Yue

NeurIPS 2020 On the Distance Between Two Neural Networks and the Stability of Learning Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu

NeurIPS 2020 Online Optimization with Memory and Competitive Control Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman

L4DC 2020 Robust Regression for Safe Exploration in Control Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue

NeurIPS 2020 The Power of Predictions in Online Control Chenkai Yu, Guanya Shi, Soon-Jo Chung, Yisong Yue, Adam Wierman

AISTATS 2019 A General Framework for Multi-Fidelity Bayesian Optimization with Gaussian Processes Jialin Song, Yuxin Chen, Yisong Yue

ICML 2019 Batch Policy Learning Under Constraints Hoang Le, Cameron Voloshin, Yisong Yue

AISTATS 2019 Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue

UAI 2019 Co-Training for Policy Learning Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono

ICML 2019 Control Regularization for Reduced Variance Reinforcement Learning Richard Cheng, Abhinav Verma, Gabor Orosz, Swarat Chaudhuri, Yisong Yue, Joel Burdick

ICLR 2019 Generating Multi-Agent Trajectories Using Programmatic Weak Supervision Eric Zhan, Stephan Zheng, Yisong Yue, Long Sha, Patrick Lucey

NeurIPS 2019 Imitation-Projected Programmatic Reinforcement Learning Abhinav Verma, Hoang Le, Yisong Yue, Swarat Chaudhuri

NeurIPS 2019 Landmark Ordinal Embedding Nikhil Ghosh, Yuxin Chen, Yisong Yue

NeurIPS 2019 NAOMI: Non-Autoregressive Multiresolution Sequence Imputation Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue

NeurIPS 2019 Teaching Multiple Concepts to a Forgetful Learner Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla

NeurIPS 2018 A General Method for Amortizing Variational Filtering Joseph Marino, Milan Cvitkovic, Yisong Yue

IJCAI 2018 Advancements in Dueling Bandits Yanan Sui, Masrour Zoghi, Katja Hofmann, Yisong Yue

ICML 2018 Hierarchical Imitation and Reinforcement Learning Hoang Le, Nan Jiang, Alekh Agarwal, Miroslav Dudik, Yisong Yue, Hal Daumé

ICML 2018 Iterative Amortized Inference Joe Marino, Yisong Yue, Stephan Mandt

AISTATS 2018 Near-Optimal Machine Teaching via Explanatory Teaching Sets Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue

AAAI 2018 Safe Exploration and Optimization of Constrained MDPs Using Gaussian Processes Akifumi Wachi, Yanan Sui, Yisong Yue, Masahiro Ono

ICML 2018 Stagewise Safe Bayesian Optimization with Gaussian Processes Yanan Sui, Vincent Zhuang, Joel Burdick, Yisong Yue

NeurIPS 2018 Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue

ICML 2017 Coordinated Multi-Agent Imitation Learning Hoang M. Le, Yisong Yue, Peter Carr, Patrick Lucey

CVPR 2017 Factorized Variational Autoencoders for Modeling Audience Reactions to Movies Zhiwei Deng, Rajitha Navarathna, Peter Carr, Stephan Mandt, Yisong Yue, Iain Matthews, Greg Mori

ICLR 2017 Learning Recurrent Representations for Hierarchical Behavior Modeling Eyrun Eyjolfsdottir, Kristin Branson, Yisong Yue, Pietro Perona

UAI 2017 Multi-Dueling Bandits with Dependent Arms Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue

NeurIPS 2016 Generating Long-Term Trajectories Using Deep Hierarchical Networks Stephan Zheng, Yisong Yue, Jennifer Hobbs

CVPR 2016 Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees Jianhui Chen, Hoang M. Le, Peter Carr, Yisong Yue, James J. Little

ICML 2016 Smooth Imitation Learning for Online Sequence Prediction Hoang Le, Andrew Kang, Yisong Yue, Peter Carr

NeurIPS 2015 Smooth Interactive Submodular Set Cover Bryan D He, Yisong Yue

ICML 2013 Learning Policies for Contextual Submodular Prediction Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, Drew Bagnell

AAAI 2012 An Efficient Simulation-Based Approach to Ambulance Fleet Allocation and Dynamic Redeployment Yisong Yue, Lavanya Marla, Ramayya Krishnan

ICML 2012 Hierarchical Exploration for Accelerating Contextual Bandits Yisong Yue, Sue Ann Hong, Carlos Guestrin

ICML 2011 Beat the Mean Bandit Yisong Yue, Thorsten Joachims

NeurIPS 2011 Linear Submodular Bandits and Their Application to Diversified Retrieval Yisong Yue, Carlos Guestrin

ICML 2009 Interactively Optimizing Information Retrieval Systems as a Dueling Bandits Problem Yisong Yue, Thorsten Joachims

COLT 2009 The K-Armed Dueling Bandits Problem Yisong Yue, Josef Broder, Robert Kleinberg, Thorsten Joachims

ICML 2008 Predicting Diverse Subsets Using Structural SVMs Yisong Yue, Thorsten Joachims