Zhe, Shandian

56 publications

TMLR 2026 StFT: Spatio-Temporal Fourier Transformer for Long-Term Dynamics Prediction Da Long, Shandian Zhe, Samuel Williams, Leonid Oliker, Zhe Bai

ICML 2025 Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation Da Long, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe

TMLR 2025 Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley, Varun Shankar, Mike Kirby, Shandian Zhe

TMLR 2025 HyResPINNs: A Hybrid Residual Physics-Informed Neural Network Architecture Designed to Balance Expressiveness and Trainability Madison Cooley, Mike Kirby, Shandian Zhe, Varun Shankar

AISTATS 2025 Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems Da Long, Zhitong Xu, Qiwei Yuan, Yin Yang, Shandian Zhe

TMLR 2025 Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data Keyan Chen, Yile Li, Da Long, Zhitong Xu, Wei W. Xing, Jacob Hochhalter, Shandian Zhe

ICLR 2025 Standard Gaussian Process Is All You Need for High-Dimensional Bayesian Optimization Zhitong Xu, Haitao Wang, Jeff M. Phillips, Shandian Zhe

ICML 2025 Toward Efficient Kernel-Based Solvers for Nonlinear PDEs Zhitong Xu, Da Long, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi

ICML 2024 BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition Shikai Fang, Qingsong Wen, Yingtao Luo, Shandian Zhe, Liang Sun

AISTATS 2024 Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels Da Long, Wei Xing, Aditi Krishnapriyan, Robert Kirby, Shandian Zhe, Michael W. Mahoney

ICLR 2024 Functional Bayesian Tucker Decomposition for Continuous-Indexed Tensor Data Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe

AISTATS 2024 Multi-Resolution Active Learning of Fourier Neural Operators Shibo Li, Xin Yu, Wei Xing, Robert Kirby, Akil Narayan, Shandian Zhe

ICLR 2024 Solving High Frequency and Multi-Scale PDEs with Gaussian Processes Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe

NeurIPS 2023 Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes Zheng Wang, Shikai Fang, Shibo Li, Shandian Zhe

ICMLW 2023 Infinite-Fidelity Surrogate Learning via High-Order Gaussian Processes Shibo Li, Li Shi, Shandian Zhe

ICML 2023 Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Mike Kirby, Shandian Zhe

AISTATS 2023 Meta-Learning with Adjoint Methods Shibo Li, Zheng Wang, Akil Narayan, Robert Kirby, Shandian Zhe

ICML 2023 Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka

NeurIPS 2023 Streaming Factor Trajectory Learning for Temporal Tensor Decomposition Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Mike Kirby, Shandian Zhe

AISTATS 2022 Deep Multi-Fidelity Active Learning of High-Dimensional Outputs Shibo Li, Zheng Wang, Robert Kirby, Shandian Zhe

AISTATS 2022 Physics Informed Deep Kernel Learning Zheng Wang, Wei Xing, Robert Kirby, Shandian Zhe

ICML 2022 AutoIP: A United Framework to Integrate Physics into Gaussian Processes Da Long, Zheng Wang, Aditi Krishnapriyan, Robert Kirby, Shandian Zhe, Michael Mahoney

NeurIPS 2022 Batch Multi-Fidelity Active Learning with Budget Constraints Shibo Li, Jeff M Phillips, Xin Yu, Robert Kirby, Shandian Zhe

ICML 2022 Bayesian Continuous-Time Tucker Decomposition Shikai Fang, Akil Narayan, Robert Kirby, Shandian Zhe

ICML 2022 Decomposing Temporal High-Order Interactions via Latent ODEs Shibo Li, Robert Kirby, Shandian Zhe

NeurIPS 2022 Infinite-Fidelity Coregionalization for Physical Simulation Shibo Li, Zheng Wang, Robert Kirby, Shandian Zhe

ICML 2022 Nonparametric Embeddings of Sparse High-Order Interaction Events Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe

ICML 2022 Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition Zheng Wang, Shandian Zhe

ICML 2022 Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes Conor Tillinghast, Zheng Wang, Shandian Zhe

NeurIPS 2022 Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm Aidan Good, Jiaqi Lin, Xin Yu, Hannah Sieg, Mikey Fergurson, Shandian Zhe, Jerzy Wieczorek, Thiago Serra

ICML 2022 The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe

AISTATS 2021 Multi-Fidelity High-Order Gaussian Processes for Physical Simulation Zheng Wang, Wei Xing, Robert Kirby, Shandian Zhe

NeurIPS 2021 Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks Shibo Li, Robert Kirby, Shandian Zhe

UAI 2021 Bayesian Streaming Sparse Tucker Decomposition Shikai Fang, Robert M. Kirby, Shandian Zhe

NeurIPS 2021 Characterizing Possible Failure Modes in Physics-Informed Neural Networks Aditi Krishnapriyan, Amir Gholami, Shandian Zhe, Robert Kirby, Michael W. Mahoney

ICML 2021 Nonparametric Decomposition of Sparse Tensors Conor Tillinghast, Shandian Zhe

NeurIPS 2021 Self-Adaptable Point Processes with Nonparametric Time Decays Zhimeng Pan, Zheng Wang, Jeff M Phillips, Shandian Zhe

ICML 2021 Streaming Bayesian Deep Tensor Factorization Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe

AAAI 2020 Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations Wei W. Xing, Shireen Y. Elhabian, Robert Michael Kirby, Ross T. Whitaker, Shandian Zhe

NeurIPS 2020 Multi-Fidelity Bayesian Optimization via Deep Neural Networks Shibo Li, Wei Xing, Robert Kirby, Shandian Zhe

IJCAI 2020 Scalable Gaussian Process Regression Networks Shibo Li, Wei W. Xing, Robert M. Kirby, Shandian Zhe

AISTATS 2020 Scalable Nonparametric Factorization for High-Order Interaction Events Zhimeng Pan, Zheng Wang, Shandian Zhe

ICML 2020 Self-Modulating Nonparametric Event-Tensor Factorization Zheng Wang, Xinqi Chu, Shandian Zhe

UAI 2020 Streaming Nonlinear Bayesian Tensor Decomposition Zhimeng Pan, Zheng Wang, Shandian Zhe

UAI 2019 Conditional Expectation Propagation Zheng Wang, Shandian Zhe

AISTATS 2019 Scalable High-Order Gaussian Process Regression Shandian Zhe, Wei Xing, Robert M. Kirby

NeurIPS 2018 Stochastic Nonparametric Event-Tensor Decomposition Shandian Zhe, Yishuai Du

ICML 2017 Asynchronous Distributed Variational Gaussian Process for Regression Hao Peng, Shandian Zhe, Xiao Zhang, Yuan Qi

AAAI 2017 Scalable Nonparametric Tensor Analysis Shandian Zhe

JAIR 2016 Association Discovery and Diagnosis of Alzheimer's Disease with Bayesian Multiview Learning Zenglin Xu, Shandian Zhe, Yuan Qi, Peng Yu

AAAI 2016 DinTucker: Scaling up Gaussian Process Models on Large Multidimensional Arrays Shandian Zhe, Yuan Qi, Youngja Park, Zenglin Xu, Ian M. Molloy, Suresh Chari

NeurIPS 2016 Distributed Flexible Nonlinear Tensor Factorization Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani

IJCAI 2016 Fast Laplace Approximation for Sparse Bayesian Spike and Slab Models Syed Abbas Zilqurnain Naqvi, Shandian Zhe, Yuan Qi, Yifan Yang, Jieping Ye

AAAI 2015 Bayesian Maximum Margin Principal Component Analysis Changying Du, Shandian Zhe, Fuzhen Zhuang, Yuan Qi, Qing He, Zhongzhi Shi

AISTATS 2015 Scalable Nonparametric Multiway Data Analysis Shandian Zhe, Zenglin Xu, Xinqi Chu, Yuan (Alan) Qi, Youngja Park

AAAI 2015 Sparse Bayesian Multiview Learning for Simultaneous Association Discovery and Diagnosis of Alzheimer's Disease Shandian Zhe, Zenglin Xu, Yuan Qi, Peng Yu