Shandian Zhe

Orcid: 0000-0003-0316-9875

According to our database1, Shandian Zhe authored at least 103 papers between 2010 and 2025.

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Bibliography

2025
ADDER: Service-Specific Adaptive Data-Driven Radio Resource Control for Cellular-IoT.
Proceedings of the 25th IEEE International Symposium on a World of Wireless, 2025

2024
Inherently interpretable machine learning solutions to differential equations.
Eng. Comput., August, 2024

Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation.
CoRR, 2024

Toward Efficient Kernel-Based Solvers for Nonlinear PDEs.
CoRR, 2024

HyResPINNs: Adaptive Hybrid Residual Networks for Learning Optimal Combinations of Neural and RBF Components for Physics-Informed Modeling.
CoRR, 2024

Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases.
CoRR, 2024

Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning.
CoRR, 2024

Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients.
CoRR, 2024

Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation.
CoRR, 2024

ElastoGen: 4D Generative Elastodynamics.
CoRR, 2024

Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems.
CoRR, 2024

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization.
CoRR, 2024

BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Solving High Frequency and Multi-Scale PDEs with Gaussian Processes.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Multi-Resolution Active Learning of Fourier Neural Operators.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions.
J. Comput. Phys., November, 2023

A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs.
J. Comput. Phys., March, 2023

Diffusion-Generative Multi-Fidelity Learning for Physical Simulation.
CoRR, 2023

BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition.
CoRR, 2023

Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations.
CoRR, 2023

Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Streaming Factor Trajectory Learning for Temporal Tensor Decomposition.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation.
Proceedings of the International Conference on Machine Learning, 2023

Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions.
Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2023

Meta-Learning with Adjoint Methods.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Multifidelity modeling for Physics-Informed Neural Networks (PINNs).
J. Comput. Phys., 2022

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks.
CoRR, 2022

A Kernel Approach for PDE Discovery and Operator Learning.
CoRR, 2022

GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices.
CoRR, 2022

Batch Multi-Fidelity Active Learning with Budget Constraints.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Infinite-Fidelity Coregionalization for Physical Simulation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition.
Proceedings of the International Conference on Machine Learning, 2022

Nonparametric Embeddings of Sparse High-Order Interaction Events.
Proceedings of the International Conference on Machine Learning, 2022

Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes.
Proceedings of the International Conference on Machine Learning, 2022

AutoIP: A United Framework to Integrate Physics into Gaussian Processes.
Proceedings of the International Conference on Machine Learning, 2022

Decomposing Temporal High-Order Interactions via Latent ODEs.
Proceedings of the International Conference on Machine Learning, 2022

Bayesian Continuous-Time Tucker Decomposition.
Proceedings of the International Conference on Machine Learning, 2022

The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022

Physics Informed Deep Kernel Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Deep Multi-Fidelity Active Learning of High-Dimensional Outputs.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Deep coregionalization for the emulation of simulation-based spatial-temporal fields.
J. Comput. Phys., 2021

Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach.
CoRR, 2021

Residual Gaussian Process: A Tractable Nonparametric Bayesian Emulator for Multi-fidelity Simulations.
CoRR, 2021

Bayesian streaming sparse Tucker decomposition.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Self-Adaptable Point Processes with Nonparametric Time Decays.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Characterizing possible failure modes in physics-informed neural networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Nonparametric Decomposition of Sparse Tensors.
Proceedings of the 38th International Conference on Machine Learning, 2021

Streaming Bayesian Deep Tensor Factorization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Multi-Fidelity High-Order Gaussian Processes for Physical Simulation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Block-term tensor neural networks.
Neural Networks, 2020

Graph constraint-based robust latent space low-rank and sparse subspace clustering.
Neural Comput. Appl., 2020

Deep Multi-Fidelity Active Learning of High-dimensional Outputs.
CoRR, 2020

Streaming Probabilistic Deep Tensor Factorization.
CoRR, 2020

Physics Regularized Gaussian Processes.
CoRR, 2020

Scalable Variational Gaussian Process Regression Networks.
CoRR, 2020

Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications.
CoRR, 2020

Streaming Nonlinear Bayesian Tensor Decomposition.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Multi-Fidelity Bayesian Optimization via Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Semantic Tree-Based 3D Scene Model Recognition.
Proceedings of the 3rd IEEE Conference on Multimedia Information Processing and Retrieval, 2020

Scalable Gaussian Process Regression Networks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Self-Modulating Nonparametric Event-Tensor Factorization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Probabilistic Neural-Kernel Tensor Decomposition.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Online Bayesian Sparse Learning with Spike and Slab Priors.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Scalable Nonparametric Factorization for High-Order Interaction Events.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Variational Random Function Model for Network Modeling.
IEEE Trans. Neural Networks Learn. Syst., 2019

Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach.
IEEE Trans. Neural Networks Learn. Syst., 2019

Deep Coregionalization for the Emulation of Spatial-Temporal Fields.
CoRR, 2019

Conditional Expectation Propagation.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Scalable High-Order Gaussian Process Regression.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition.
Cogn. Comput., 2018

Stochastic Nonparametric Event-Tensor Decomposition.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Probabilistic Streaming Tensor Decomposition.
Proceedings of the IEEE International Conference on Data Mining, 2018

Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Data-driven resource flexing for network functions visualization.
Proceedings of the 2018 Symposium on Architectures for Networking and Communications Systems, 2018

2017
Scalable Bayesian Nonparametrics and Sparse Learning for Hidden Relationship Discovery
PhD thesis, 2017

DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates.
Bioinform., 2017

Learning from semantically dependent multi-tasks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Asynchronous Distributed Variational Gaussian Process for Regression.
Proceedings of the 34th International Conference on Machine Learning, 2017

Scalable Nonparametric Tensor Analysis.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Association Discovery and Diagnosis of Alzheimer's Disease with Bayesian Multiview Learning.
J. Artif. Intell. Res., 2016

SWATShare - A web platform for collaborative research and education through online sharing, simulation and visualization of SWAT models.
Environ. Model. Softw., 2016

Distributed Flexible Nonlinear Tensor Factorization.
CoRR, 2016

Bayesian Group Feature Selection for Support Vector Learning Machines.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Distributed Flexible Nonlinear Tensor Factorization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Annealed Sparsity via Adaptive and Dynamic Shrinking.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Fast Laplace Approximation for Sparse Bayesian Spike and Slab Models.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

DinTucker: Scaling Up Gaussian Process Models on Large Multidimensional Arrays.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Scalable Nonparametric Multiway Data Analysis.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Sparse Bayesian Multiview Learning for Simultaneous Association Discovery and Diagnosis of Alzheimer's Disease.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Bayesian Maximum Margin Principal Component Analysis.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Joint Association Discovery and Diagnosis of Alzheimer's Disease by Supervised Heterogeneous Multiview Learning.
Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

2013
Supervised Heterogeneous Multiview Learning for Joint Association Study and Disease Diagnosis
CoRR, 2013

DinTucker: Scaling up Gaussian process models on multidimensional arrays with billions of elements.
CoRR, 2013

Joint network and node selection for pathway-based genomic data analysis.
Bioinform., 2013

2011
Conditional Random Fields for Machine Translation System Combination.
Int. J. Asian Lang. Process., 2011

2010
Modeling Users' Information Goal Transitions and Satisfaction Judgment: Understanding the Full Search Process.
Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence, 2010

Conditional Random Fields for Machine Translation System Combination.
Proceedings of the International Conference on Asian Language Processing, 2010


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