Shan-Dian Zhe

Most-cited papers

Characterizing possible failure modes in physics-informed neural networks
Aditi S. Krishnapriyan, A. Gholami, Shan-Dian Zhe, Robert M. Kirby +1 more
2021Neural Information Processing Systems1,474 citations
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A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions
Michael Penwarden, Ameya Dilip Jagtap, Shan-Dian Zhe, G. Karniadakis +1 more
2023Journal of Computational Physics135 citations Open access
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Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications
Yun Yuan, Zhao Zhang, Xian-Feng Yang, Shan-Dian Zhe
2020Transportation Research Part B: Methodological120 citations Open access
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A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs
Michael Penwarden, Shan-Dian Zhe, A. Narayan, Robert M. Kirby
2021Journal of Computational Physics89 citations Open access
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Multifidelity Modeling for Physics-Informed Neural Networks (PINNs)
Michael Penwarden, Shan-Dian Zhe, A. Narayan, Robert M. Kirby
2021Journal of Computational Physics77 citations Open access
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Multi-Fidelity Bayesian Optimization via Deep Neural Networks
Shibo Li, Wei W. Xing, R. Kirby, Shan-Dian Zhe
2020Neural Information Processing Systems74 citations
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The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks
Xin Yu, Thiago Serra, S. Ramalingam, Shan-Dian Zhe
2022International Conference on Machine Learning67 citations Open access
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Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
Zhitong Xu, Hai-Tao Wang, Jeff M. Phillips, Shan-Dian Zhe
2024International Conference on Learning Representations48 citations
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Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
Yu Chen, Wei Deng, Shikai Fang, Fengpei Li +6 more
2023International Conference on Machine Learning40 citations Open access
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Block-term tensor neural networks
Jinmian Ye, Guangxi Li, Di Chen, Haiqin Yang +2 more
2020Neural Networks37 citations Open access
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Multi-Resolution Active Learning of Fourier Neural Operators
Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby +2 more
2023International Conference on Artificial Intelligence and Statistics33 citations Open access
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Deep Multi-Fidelity Active Learning of High-dimensional Outputs
Shibo Li, Zheng Wang, R. Kirby, Shan-Dian Zhe
2020International Conference on Artificial Intelligence and Statistics33 citations
Semantic Scholar
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
Da Long, Z. Wang, Aditi S. Krishnapriyan, Robert M. Kirby +2 more
2022International Conference on Machine Learning28 citations
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Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems
Da Long, Zhitong Xu, Qi-Wei Yuan, Yin Yang +1 more
2024International Conference on Artificial Intelligence and Statistics26 citations
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Bayesian streaming sparse Tucker decomposition
Shikai Fang, Robert M. Kirby, Shan-Dian Zhe
2021Conference on Uncertainty in Artificial Intelligence26 citations
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Development and validation of a machine learning method to predict intraoperative red blood cell transfusions in cardiothoracic surgery
Z. Wang, Shan-Dian Zhe, Josh Zimmerman, Candice Morrisey +3 more
2022Scientific Reports25 citations Open access
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Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
Zheng Wang, Wei W. Xing, R. Kirby, Shan-Dian Zhe
2020International Conference on Artificial Intelligence and Statistics25 citations
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BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition
Shikai Fang, Qingsong Wen, Yingtao Luo, Shan-Dian Zhe +1 more
2023International Conference on Machine Learning24 citations Open access
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Bayesian Continuous-Time Tucker Decomposition
Shikai Fang, A. Narayan, Robert M. Kirby, Shan-Dian Zhe
2022International Conference on Machine Learning23 citations
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Batch Multi-Fidelity Active Learning with Budget Constraints
Shibo Li, J. M. Phillips, Xin Yu, Robert M. Kirby +1 more
2022Neural Information Processing Systems23 citations Open access
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Probabilistic Neural-Kernel Tensor Decomposition
Conor Tillinghast, Shikai Fang, Kai Zhang, Shan-Dian Zhe
2020Industrial Conference on Data Mining22 citations
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Residual Gaussian Process: A Tractable Nonparametric Bayesian Emulator for Multi-fidelity Simulations
Wei W. Xing, A. Shah, Peng Wang, Shan-Dian Zhe +2 more
2021arXiv.org21 citations Open access
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Physics Informed Deep Kernel Learning
Z. Wang, Wei W. Xing, Robert Kirby, Shan-Dian Zhe
2020International Conference on Artificial Intelligence and Statistics21 citations
Semantic Scholar
Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach
Michael Penwarden, Shan-Dian Zhe, A. Narayan, Robert M. Kirby
2021Social Science Research Network20 citations Open access
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Streaming Bayesian Deep Tensor Factorization
Shikai Fang, Z. Wang, Zhi-Meng Pan, Ji Liu +1 more
2021International Conference on Machine Learning19 citations
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Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
Shikai Fang, Madison Cooley, Da Long, Shi-Bo Li +2 more
2023International Conference on Learning Representations17 citations
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Streaming Nonlinear Bayesian Tensor Decomposition
Zhi-Meng Pan, Z. Wang, Shan-Dian Zhe
2020Conference on Uncertainty in Artificial Intelligence17 citations
Semantic Scholar
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm
Aidan Good, Jia-Qi Lin, H. Sieg, Mikey Ferguson +4 more
2022Neural Information Processing Systems15 citations Open access
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Physics Regularized Gaussian Processes
Zheng Wang, Wei W. Xing, R. Kirby, Shan-Dian Zhe
2020arXiv.org15 citations
Semantic Scholar
The Development and Use of AI Chatbots for Health Behavior Change: Scoping Review
Ling-Yi Fu, Ryan D. Burns, Yu-Huan Xie, Jincheng Shen +3 more
2025Journal of Medical Internet Research14 citations
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Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks
Shi-Bo Li, Robert M. Kirby, Shan-Dian Zhe
2021Neural Information Processing Systems14 citations
Semantic Scholar
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases
Madison Cooley, Varun Shankar, R. M. Kirby, Shan-Dian Zhe
2024Trans. Mach. Learn. Res.13 citations
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Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data
Shikai Fang, Xin Yu, Zheng Wang, Shi-Bo Li +2 more
2023International Conference on Learning Representations13 citations
Semantic Scholar
Self-Adaptable Point Processes with Nonparametric Time Decays
Zhi-Meng Pan, Z. Wang, J. M. Phillips, Shan-Dian Zhe
2021Neural Information Processing Systems13 citations
Semantic Scholar
A kernel framework for learning differential equations and their solution operators
Da Long, Nicole Mrvaljević, Shan-Dian Zhe, Bamdad Hosseini
2024Physica A: Statistical Mechanics and its Applications12 citations Open access
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Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
Matthew Lowery, John Turnage, Zachary Morrow, J. Jakeman +3 more
2024Trans. Mach. Learn. Res.12 citations
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Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
Zhitong Xu, Da Long, Yiming Xu, Guang Yang +2 more
2024International Conference on Machine Learning12 citations
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Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes
Zheng Wang, Shikai Fang, Shi-Bo Li, Shan-Dian Zhe
2023Neural Information Processing Systems12 citations
Semantic Scholar
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
Shikai Fang, Xin Yu, Shi-Bo Li, Zheng Wang +2 more
2023Neural Information Processing Systems12 citations
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Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions
Jun-Yang Cai, Khai-Nguyen Nguyen, Nishant Shrestha, Aidan Good +4 more
2023Integration of AI and OR Techniques in Constraint Programming12 citations Open access
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Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes
Conor Tillinghast, Z. Wang, Shan-Dian Zhe
2021International Conference on Machine Learning12 citations
Semantic Scholar
Deep coregionalization for the emulation of simulation-based spatial-temporal fields
Wei W. Xing, R. Kirby, Shan-Dian Zhe
2020Journal of Computational Physics12 citations Open access
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ElastoGen: 4D Generative Elastodynamics
Yutao Feng, Yintong Shang, Xiang Feng, Lei Lan +7 more
2024AAAI Conference on Artificial Intelligence11 citations
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Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations
Hongsup Oh, R. Amici, Geoffrey Bomarito, Shan-Dian Zhe +2 more
2023arXiv.org11 citations Open access
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Scalable Nonparametric Factorization for High-Order Interaction Events
Zhi-Meng Pan, Zheng Wang, Shan-Dian Zhe
2020International Conference on Artificial Intelligence and Statistics11 citations
Semantic Scholar
Self-Modulating Nonparametric Event-Tensor Factorization
Zheng Wang, Xinqi Chu, Shan-Dian Zhe
2020International Conference on Machine Learning11 citations
Semantic Scholar
Multi-Omic Integration of Blood-Based Tumor-Associated Genomic and Lipidomic Profiles Using Machine Learning Models in Metastatic Prostate Cancer
Shikai Fang, Shan-Dian Zhe, Hui-Ming Lin, A. Azad +9 more
2023JCO Clinical Cancer Informatics10 citations Open access
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Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition
Z. Wang, Shan-Dian Zhe
2022International Conference on Machine Learning10 citations Open access
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A Kernel Approach for PDE Discovery and Operator Learning
Da Long, Nicole Mrvaljević, Shan-Dian Zhe, Bamdad Hosseini
2022arXiv.org10 citations Open access
Semantic Scholar
Infinite-Fidelity Coregionalization for Physical Simulation
Shi-Bo Li, Z. Wang, Robert M. Kirby, Shan-Dian Zhe
2022Neural Information Processing Systems10 citations Open access
Semantic Scholar