Shandian Zhe

ORCID

Publication Activity (10 Years)

Years Active: 2010-2025
Publications (10 Years): 112

Top Venues

Publications

Yingjing Wu, Ahmed Elmokashfi, Foivos Michelinakis, Jacobus E. van der Merwe, Shandian Zhe
ADDER: Service-Specific Adaptive Data-Driven Radio Resource Control for Cellular-IoT. WoWMoM (2025)
Da Long, Shandian Zhe
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems. CoRR (2024)
Zachary Bastiani, Robert M. Kirby, Jacob D. Hochhalter, Shandian Zhe
Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients. CoRR (2024)
Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan, Shandian Zhe
Multi-Resolution Active Learning of Fourier Neural Operators. AISTATS (2024)
Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. AISTATS (2024)
Madison Cooley, Shandian Zhe, Robert M. Kirby, Varun Shankar
Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation. CoRR (2024)
Yutao Feng, Yintong Shang, Xiang Feng, Lei Lan, Shandian Zhe, Tianjia Shao, Hongzhi Wu, Kun Zhou, Hao Su, Chenfanfu Jiang, Yin Yang
ElastoGen: 4D Generative Elastodynamics. CoRR (2024)
Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. ICLR (2024)
Matthew Lowery, John Turnage, Zachary Morrow, John D. Jakeman, Akil Narayan, Shandian Zhe, Varun Shankar
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning. CoRR (2024)
Zhitong Xu, Shandian Zhe
Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization. CoRR (2024)
Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data. ICLR (2024)
Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. CoRR (2023)
Zheng Wang, Shikai Fang, Shibo Li, Shandian Zhe
Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes. NeurIPS (2023)
Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. CoRR (2023)
Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha, Aidan Good, Ruisen Tu, Xin Yu, Shandian Zhe, Thiago Serra
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions. CPAIOR (2023)
Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Mike Kirby, Shandian Zhe
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. NeurIPS (2023)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs. J. Comput. Phys. 477 (2023)
Shibo Li, Zheng Wang, Akil Narayan, Robert M. Kirby, Shandian Zhe
Meta-Learning with Adjoint Methods. AISTATS (2023)
Zheng Wang, Shibo Li, Shikai Fang, Shandian Zhe
Diffusion-Generative Multi-Fidelity Learning for Physical Simulation. CoRR (2023)
Shibo Li, Xin Yu, Wei W. Xing, Mike Kirby, Akil Narayan, Shandian Zhe
Multi-Resolution Active Learning of Fourier Neural Operators. CoRR (2023)
Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Mike Kirby, Shandian Zhe
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. ICML (2023)
Shikai Fang, Madison Cooley, Da Long, Shibo Li, Robert M. Kirby, Shandian Zhe
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. CoRR (2023)
Shikai Fang, Qingsong Wen, Shandian Zhe, Liang Sun
BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition. CoRR (2023)
Hongsup Oh, Roman Amici, Geoffrey F. Bomarito, Shandian Zhe, Robert Kirby, Jacob D. Hochhalter
Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations. CoRR (2023)
Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. ICML (2023)
Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. CoRR (2023)
Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. CoRR (2023)
Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha, Aidan Good, Ruisen Tu, Xin Yu, Shandian Zhe, Thiago Serra
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions. CoRR (2023)
Zheng Wang, Shikai Fang, Shibo Li, Shandian Zhe
Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes. CoRR (2023)
Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data. CoRR (2023)
Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. J. Comput. Phys. 493 (2023)
Zheng Wang, Shandian Zhe
Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition. CoRR (2022)
Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Infinite-Fidelity Coregionalization for Physical Simulation. CoRR (2022)
Zheng Wang, Shandian Zhe
Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition. ICML (2022)
Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
AutoIP: A United Framework to Integrate Physics into Gaussian Processes. CoRR (2022)
Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. CoRR (2022)
Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Active Learning with Budget Constraints. CoRR (2022)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Multifidelity modeling for Physics-Informed Neural Networks (PINNs). J. Comput. Phys. 451 (2022)
Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Infinite-Fidelity Coregionalization for Physical Simulation. NeurIPS (2022)
Conor Tillinghast, Zheng Wang, Shandian Zhe
Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes. ICML (2022)
Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
Nonparametric Embeddings of Sparse High-Order Interaction Events. CoRR (2022)
Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. CoRR (2022)
Aidan Good, Jiaqi Lin, Xin Yu, Hannah Sieg, Mikey Ferguson, Shandian Zhe, Jerzy Wieczorek, Thiago Serra
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. NeurIPS (2022)
Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. ICML (2022)
Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Active Learning with Budget Constraints. NeurIPS (2022)
Shikai Fang, Akil Narayan, Robert M. Kirby, Shandian Zhe
Bayesian Continuous-Time Tucker Decomposition. ICML (2022)
Shibo Li, Michael Penwarden, Robert M. Kirby, Shandian Zhe
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. CoRR (2022)
Da Long, Nicole Mrvaljevic, Shandian Zhe, Bamdad Hosseini
A Kernel Approach for PDE Discovery and Operator Learning. CoRR (2022)
Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Deep Multi-Fidelity Active Learning of High-Dimensional Outputs. AISTATS (2022)
Zheng Wang, Wei Xing, Robert M. Kirby, Shandian Zhe
Physics Informed Deep Kernel Learning. AISTATS (2022)
Shibo Li, Robert Kirby, Shandian Zhe
Decomposing Temporal High-Order Interactions via Latent ODEs. ICML (2022)
Vahid Keshavarzzadeh, Shandian Zhe, Robert M. Kirby, Akil Narayan
GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices. CoRR (2022)
Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
AutoIP: A United Framework to Integrate Physics into Gaussian Processes. ICML (2022)
Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
Nonparametric Embeddings of Sparse High-Order Interaction Events. ICML (2022)
Shibo Li, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. NeurIPS (2021)
Wei W. Xing, Akeel A. Shah, Peng Wang, Shandian Zhe, Qian Fu, Robert M. Kirby
Residual Gaussian Process: A Tractable Nonparametric Bayesian Emulator for Multi-fidelity Simulations. CoRR (2021)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Multifidelity Modeling for Physics-Informed Neural Networks (PINNs). CoRR (2021)
Shikai Fang, Robert M. Kirby, Shandian Zhe
Bayesian streaming sparse Tucker decomposition. UAI (2021)
Shibo Li, Zheng Wang, Akil Narayan, Robert Michael Kirby, Shandian Zhe
Meta-Learning with Adjoint Methods. CoRR (2021)
Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe
Streaming Bayesian Deep Tensor Factorization. ICML (2021)
Conor Tillinghast, Zheng Wang, Shandian Zhe
Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes. CoRR (2021)
Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
Characterizing possible failure modes in physics-informed neural networks. CoRR (2021)
Shibo Li, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. CoRR (2021)
Conor Tillinghast, Shandian Zhe
Nonparametric Decomposition of Sparse Tensors. ICML (2021)
Zhimeng Pan, Zheng Wang, Jeff M. Phillips, Shandian Zhe
Self-Adaptable Point Processes with Nonparametric Time Decays. NeurIPS (2021)
Wei W. Xing, Robert M. Kirby, Shandian Zhe
Deep coregionalization for the emulation of simulation-based spatial-temporal fields. J. Comput. Phys. 428 (2021)
Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
Characterizing possible failure modes in physics-informed neural networks. NeurIPS (2021)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach. CoRR (2021)
Zheng Wang, Wei Xing, Robert Michael Kirby, Shandian Zhe
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation. AISTATS (2021)
Zheng Wang, Wei Xing, Robert Michael Kirby, Shandian Zhe
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation. CoRR (2020)
Wei Xing, Shireen Y. Elhabian, Robert Michael Kirby, Ross T. Whitaker, Shandian Zhe
Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations. AAAI (2020)
Jinmian Ye, Guangxi Li, Di Chen, Haiqin Yang, Shandian Zhe, Zenglin Xu
Block-term Tensor Neural Networks. CoRR (2020)
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe
Multi-Fidelity Bayesian Optimization via Deep Neural Networks. NeurIPS (2020)
Shibo Li, Wei Xing, Mike Kirby, Shandian Zhe
Multi-Fidelity Bayesian Optimization via Deep Neural Networks. CoRR (2020)
Jinmian Ye, Guangxi Li, Di Chen, Haiqin Yang, Shandian Zhe, Zenglin Xu
Block-term tensor neural networks. Neural Networks 130 (2020)
Shibo Li, Wei Xing, Mike Kirby, Shandian Zhe
Scalable Variational Gaussian Process Regression Networks. CoRR (2020)
Zheng Wang, Wei Xing, Robert Michael Kirby, Shandian Zhe
Physics Regularized Gaussian Processes. CoRR (2020)
Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe
Streaming Probabilistic Deep Tensor Factorization. CoRR (2020)
Yun Yuan, Xianfeng Terry Yang, Zhao Zhang, Shandian Zhe
Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications. CoRR (2020)
Juefei Yuan, Tianyang Wang, Shandian Zhe, Yijuan Lu, Bo Li
Semantic Tree-Based 3D Scene Model Recognition. MIPR (2020)
Shikai Fang, Shandian Zhe, Kuang-chih Lee, Kai Zhang, Jennifer Neville
Online Bayesian Sparse Learning with Spike and Slab Priors. ICDM (2020)
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe
Scalable Gaussian Process Regression Networks. IJCAI (2020)
Yunjun Xiao, Jia Wei, Jiabing Wang, Qianli Ma, Shandian Zhe, Tolga Tasdizen
Graph constraint-based robust latent space low-rank and sparse subspace clustering. Neural Comput. Appl. 32 (12) (2020)
Zheng Wang, Xinqi Chu, Shandian Zhe
Self-Modulating Nonparametric Event-Tensor Factorization. ICML (2020)
Zhimeng Pan, Zheng Wang, Shandian Zhe
Streaming Nonlinear Bayesian Tensor Decomposition. UAI (2020)
Zhimeng Pan, Zheng Wang, Shandian Zhe
Scalable Nonparametric Factorization for High-Order Interaction Events. AISTATS (2020)
Conor Tillinghast, Shikai Fang, Kai Zhang, Shandian Zhe
Probabilistic Neural-Kernel Tensor Decomposition. ICDM (2020)
Shibo Li, Robert M. Kirby, Shandian Zhe
Deep Multi-Fidelity Active Learning of High-dimensional Outputs. CoRR (2020)
Zheng Wang, Shandian Zhe
Conditional Expectation Propagation. UAI (2019)
Liang Lan, Zhuang Wang, Shandian Zhe, Wei Cheng, Jun Wang, Kai Zhang
Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach. IEEE Trans. Neural Networks Learn. Syst. 30 (2) (2019)
Shandian Zhe, Wei Xing, Robert M. Kirby
Scalable High-Order Gaussian Process Regression. AISTATS (2019)
Zenglin Xu, Bin Liu, Shandian Zhe, Haoli Bai, Zihan Wang, Jennifer Neville
Variational Random Function Model for Network Modeling. IEEE Trans. Neural Networks Learn. Syst. 30 (1) (2019)
Zheng Wang, Shandian Zhe
Conditional Expectation Propagation. CoRR (2019)
Wei Xing, Robert M. Kirby, Shandian Zhe
Deep Coregionalization for the Emulation of Spatial-Temporal Fields. CoRR (2019)
Jinmian Ye, Linnan Wang, Guangxi Li, Di Chen, Shandian Zhe, Xinqi Chu, Zenglin Xu
Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition. CVPR (2018)
Yishuai Du, Yimin Zheng, Kuang-chih Lee, Shandian Zhe
Probabilistic Streaming Tensor Decomposition. ICDM (2018)
Lianjie Cao, Sonia Fahmy, Puneet Sharma, Shandian Zhe
Data-driven resource flexing for network functions visualization. ANCS (2018)
Shandian Zhe, Yishuai Du
Stochastic Nonparametric Event-Tensor Decomposition. NeurIPS (2018)
Bin Liu, Lirong He, Yingming Li, Shandian Zhe, Zenglin Xu
NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition. Cogn. Comput. 10 (6) (2018)
Hao Peng, Shandian Zhe, Xiao Zhang, Yuan Qi
Asynchronous Distributed Variational Gaussian Process for Regression. ICML (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Shandian Zhe