Shandian Zhe - RankMe

148 papers A* 42A 13B 2C 1Misc 1Journal 82Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	ElastoGen: 4D Generative Elastodynamics. AAAI Yutao Feng, Yintong Shang, Xiang Feng, Lei Lan, Shandian Zhe, Tianjia Shao, Hongzhi Wu, Kun Zhou, Chenfanfu Jiang, Yin Yang
2026	J	`jnl`	Kronecker-Structured Nonparametric Spatiotemporal Point Processes. CoRR Zhitong Xu, Qiwei Yuan, Yinghao Chen, Yan Sun, Bin Shen, Shandian Zhe
2026	J	`jnl`	StFT: Spatio-temporal Fourier Transformer for Long-term Dynamics Prediction. Trans. Mach. Learn. Res. Da Long, Shandian Zhe, Samuel Williams, Leonid Oliker, Zhe Bai
2025	J	`jnl`	A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications. CoRR Krishna Prasath Logakannan, Shridhar Vashishtha, Jacob D. Hochhalter, Shandian Zhe, Robert M. Kirby
2025	C	`conf`	ADDER: Service-Specific Adaptive Data-Driven Radio Resource Control for Cellular-IoT. WoWMoM Yingjing Wu, Ahmed Elmokashfi, Foivos Michelinakis, Jacobus E. van der Merwe, Shandian Zhe
2025	A*	`conf`	Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation. ICML Da Long, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe
2025	J	`jnl`	Deep Gaussian Processes for Functional Maps. CoRR Matthew Lowery, Zhitong Xu, Da Long, Keyan Chen, Daniel S. Johnson, Yang Bai, Varun Shankar, Shandian Zhe
2025	J	`jnl`	Diffusion-Based Symbolic Regression. CoRR Zachary Bastiani, Robert M. Kirby, Jacob D. Hochhalter, Shandian Zhe
2025	J	`jnl`	Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases. Trans. Mach. Learn. Res. Madison Cooley, Varun Shankar, Mike Kirby, Shandian Zhe
2025	J	`jnl`	Graph-Based Operator Learning from Limited Data on Irregular Domains. CoRR Yile Li, Shandian Zhe
2025	J	`jnl`	HyResPINNs: A Hybrid Residual Physics-Informed Neural Network Architecture Designed to Balance Expressiveness and Trainability. Trans. Mach. Learn. Res. Madison Cooley, Mike Kirby, Shandian Zhe, Varun Shankar
2025	A	`conf`	Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems. AISTATS Da Long, Zhitong Xu, Qiwei Yuan, Yin Yang, Shandian Zhe
2025	J	`jnl`	Multi-Operator Few-Shot Learning for Generalization Across PDE Families. CoRR Yile Li, Shandian Zhe
2025	J	`jnl`	Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data. CoRR Keyan Chen, Yile Li, Da Long, Zhitong Xu, Wei Xing, Jacob D. Hochhalter, Shandian Zhe
2025	J	`jnl`	Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data. Trans. Mach. Learn. Res. Keyan Chen, Yile Li, Da Long, Zhitong Xu, Wei W. Xing, Jacob D. Hochhalter, Shandian Zhe
2025	J	`jnl`	SIFBench: An Extensive Benchmark for Fatigue Analysis. CoRR Tushar Gautam, Robert M. Kirby, Jacob D. Hochhalter, Shandian Zhe
2025	J	`jnl`	Spatio-temporal Fourier Transformer (StFT) for Long-term Dynamics Prediction. CoRR Da Long, Shandian Zhe, Samuel Williams, Leonid Oliker, Zhe Bai
2025	A*	`conf`	Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization. ICLR Zhitong Xu, Haitao Wang, Jeff M. Phillips, Shandian Zhe
2025	J	`jnl`	Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs. CoRR Qiwei Yuan, Zhitong Xu, Yinghao Chen, Yiming Xu, Houman Owhadi, Shandian Zhe
2025	A*	`conf`	Toward Efficient Kernel-Based Solvers for Nonlinear PDEs. ICML Zhitong Xu, Da Long, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi
2024	J	`jnl`	Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation. CoRR Da Long, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe
2024	A*	`conf`	BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition. ICML Shikai Fang, Qingsong Wen, Yingtao Luo, Shandian Zhe, Liang Sun
2024	J	`jnl`	Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients. CoRR Zachary Bastiani, Robert M. Kirby, Jacob D. Hochhalter, Shandian Zhe
2024	J	`jnl`	ElastoGen: 4D Generative Elastodynamics. CoRR Yutao Feng, Yintong Shang, Xiang Feng, Lei Lan, Shandian Zhe, Tianjia Shao, Hongzhi Wu, Kun Zhou, Hao Su, Chenfanfu Jiang, Yin Yang
2024	A	`conf`	Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. AISTATS Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
2024	J	`jnl`	Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases. CoRR Madison Cooley, Varun Shankar, Robert M. Kirby, Shandian Zhe
2024	A*	`conf`	Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data. ICLR Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe
2024	J	`jnl`	HyResPINNs: Adaptive Hybrid Residual Networks for Learning Optimal Combinations of Neural and RBF Components for Physics-Informed Modeling. CoRR Madison Cooley, Robert M. Kirby, Shandian Zhe, Varun Shankar
2024	J	`jnl`	Inherently interpretable machine learning solutions to differential equations. Eng. Comput. Hongsup Oh, Roman Amici, Geoffrey F. Bomarito, Shandian Zhe, Robert M. Kirby, Jacob D. Hochhalter
2024	J	`jnl`	Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems. CoRR Da Long, Shandian Zhe
2024	J	`jnl`	Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning. CoRR Matthew Lowery, John Turnage, Zachary Morrow, John D. Jakeman, Akil Narayan, Shandian Zhe, Varun Shankar
2024	A	`conf`	Multi-Resolution Active Learning of Fourier Neural Operators. AISTATS Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan, Shandian Zhe
2024	J	`jnl`	Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation. CoRR Madison Cooley, Shandian Zhe, Robert M. Kirby, Varun Shankar
2024	A*	`conf`	Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. ICLR Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe
2024	J	`jnl`	Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization. CoRR Zhitong Xu, Shandian Zhe
2024	J	`jnl`	Toward Efficient Kernel-Based Solvers for Nonlinear PDEs. CoRR Zhitong Xu, Da Long, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi
2023	J	`jnl`	A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs. J. Comput. Phys. Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2023	J	`jnl`	A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. CoRR Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
2023	J	`jnl`	A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. J. Comput. Phys. Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
2023	J	`jnl`	BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition. CoRR Shikai Fang, Qingsong Wen, Shandian Zhe, Liang Sun
2023	J	`jnl`	Diffusion-Generative Multi-Fidelity Learning for Physical Simulation. CoRR Zheng Wang, Shibo Li, Shikai Fang, Shandian Zhe
2023	A*	`conf`	Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes. NeurIPS Zheng Wang, Shikai Fang, Shibo Li, Shandian Zhe
2023	J	`jnl`	Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes. CoRR Zheng Wang, Shikai Fang, Shibo Li, Shandian Zhe
2023	J	`jnl`	Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. CoRR Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
2023	J	`jnl`	Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data. CoRR Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe
2023	J	`jnl`	Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations. CoRR Hongsup Oh, Roman Amici, Geoffrey F. Bomarito, Shandian Zhe, Robert M. Kirby, Jacob D. Hochhalter
2023	B	`conf`	Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions. CPAIOR Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha, Aidan Good, Ruisen Tu, Xin Yu, Shandian Zhe, Thiago Serra
2023	J	`jnl`	Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions. CoRR Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha, Aidan Good, Ruisen Tu, Xin Yu, Shandian Zhe, Thiago Serra
2023	A*	`conf`	Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. ICML Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Mike Kirby, Shandian Zhe
2023	A	`conf`	Meta-Learning with Adjoint Methods. AISTATS Shibo Li, Zheng Wang, Akil Narayan, Robert M. Kirby, Shandian Zhe
2023	J	`jnl`	Multi-Resolution Active Learning of Fourier Neural Operators. CoRR Shibo Li, Xin Yu, Wei W. Xing, Mike Kirby, Akil Narayan, Shandian Zhe
2023	A*	`conf`	Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. ICML Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
2023	J	`jnl`	Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. CoRR Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
2023	J	`jnl`	Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. CoRR Shikai Fang, Madison Cooley, Da Long, Shibo Li, Robert M. Kirby, Shandian Zhe
2023	A*	`conf`	Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. NeurIPS Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Mike Kirby, Shandian Zhe
2023	J	`jnl`	Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. CoRR Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	A Kernel Approach for PDE Discovery and Operator Learning. CoRR Da Long, Nicole Mrvaljevic, Shandian Zhe, Bamdad Hosseini
2022	A*	`conf`	AutoIP: A United Framework to Integrate Physics into Gaussian Processes. ICML Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
2022	J	`jnl`	AutoIP: A United Framework to Integrate Physics into Gaussian Processes. CoRR Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
2022	A*	`conf`	Batch Multi-Fidelity Active Learning with Budget Constraints. NeurIPS Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	Batch Multi-Fidelity Active Learning with Budget Constraints. CoRR Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe
2022	A*	`conf`	Bayesian Continuous-Time Tucker Decomposition. ICML Shikai Fang, Akil Narayan, Robert M. Kirby, Shandian Zhe
2022	A*	`conf`	Decomposing Temporal High-Order Interactions via Latent ODEs. ICML Shibo Li, Robert M. Kirby, Shandian Zhe
2022	A	`conf`	Deep Multi-Fidelity Active Learning of High-Dimensional Outputs. AISTATS Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices. CoRR Vahid Keshavarzzadeh, Shandian Zhe, Robert M. Kirby, Akil Narayan
2022	A*	`conf`	Infinite-Fidelity Coregionalization for Physical Simulation. NeurIPS Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	Infinite-Fidelity Coregionalization for Physical Simulation. CoRR Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. CoRR Shibo Li, Michael Penwarden, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	Multifidelity modeling for Physics-Informed Neural Networks (PINNs). J. Comput. Phys. Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2022	A*	`conf`	Nonparametric Embeddings of Sparse High-Order Interaction Events. ICML Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
2022	J	`jnl`	Nonparametric Embeddings of Sparse High-Order Interaction Events. CoRR Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
2022	A*	`conf`	Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition. ICML Zheng Wang, Shandian Zhe
2022	J	`jnl`	Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition. CoRR Zheng Wang, Shandian Zhe
2022	A*	`conf`	Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes. ICML Conor Tillinghast, Zheng Wang, Shandian Zhe
2022	A	`conf`	Physics Informed Deep Kernel Learning. AISTATS Zheng Wang, Wei W. Xing, Robert M. Kirby, Shandian Zhe
2022	A*	`conf`	Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. NeurIPS Aidan Good, Jiaqi Lin, Xin Yu, Hannah Sieg, Mikey Ferguson, Shandian Zhe, Jerzy Wieczorek, Thiago Serra
2022	J	`jnl`	Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. CoRR Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra
2022	A*	`conf`	The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. ICML Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe
2022	J	`jnl`	The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. CoRR Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe
2021	A*	`conf`	Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. NeurIPS Shibo Li, Robert M. Kirby, Shandian Zhe
2021	J	`jnl`	Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. CoRR Shibo Li, Robert M. Kirby, Shandian Zhe
2021	A	`conf`	Bayesian streaming sparse Tucker decomposition. UAI Shikai Fang, Robert M. Kirby, Shandian Zhe
2021	A*	`conf`	Characterizing possible failure modes in physics-informed neural networks. NeurIPS Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
2021	J	`jnl`	Characterizing possible failure modes in physics-informed neural networks. CoRR Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
2021	J	`jnl`	Deep coregionalization for the emulation of simulation-based spatial-temporal fields. J. Comput. Phys. Wei W. Xing, Robert M. Kirby, Shandian Zhe
2021	J	`jnl`	Meta-Learning with Adjoint Methods. CoRR Shibo Li, Zheng Wang, Akil Narayan, Robert Michael Kirby, Shandian Zhe
2021	A	`conf`	Multi-Fidelity High-Order Gaussian Processes for Physical Simulation. AISTATS Zheng Wang, Wei W. Xing, Robert Michael Kirby, Shandian Zhe
2021	J	`jnl`	Multifidelity Modeling for Physics-Informed Neural Networks (PINNs). CoRR Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2021	A*	`conf`	Nonparametric Decomposition of Sparse Tensors. ICML Conor Tillinghast, Shandian Zhe
2021	J	`jnl`	Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes. CoRR Conor Tillinghast, Zheng Wang, Shandian Zhe
2021	J	`jnl`	Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach. CoRR Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2021	J	`jnl`	Residual Gaussian Process: A Tractable Nonparametric Bayesian Emulator for Multi-fidelity Simulations. CoRR Wei W. Xing, Akeel A. Shah, Peng Wang, Shandian Zhe, Qian Fu, Robert M. Kirby
2021	A*	`conf`	Self-Adaptable Point Processes with Nonparametric Time Decays. NeurIPS Zhimeng Pan, Zheng Wang, Jeff M. Phillips, Shandian Zhe
2021	A*	`conf`	Streaming Bayesian Deep Tensor Factorization. ICML Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe
2020	J	`jnl`	Block-term Tensor Neural Networks. CoRR Jinmian Ye, Guangxi Li, Di Chen, Haiqin Yang, Shandian Zhe, Zenglin Xu
2020	J	`jnl`	Block-term tensor neural networks. Neural Networks Jinmian Ye, Guangxi Li, Di Chen, Haiqin Yang, Shandian Zhe, Zenglin Xu
2020	J	`jnl`	Deep Multi-Fidelity Active Learning of High-dimensional Outputs. CoRR Shibo Li, Robert M. Kirby, Shandian Zhe
2020	J	`jnl`	Graph constraint-based robust latent space low-rank and sparse subspace clustering. Neural Comput. Appl. Yunjun Xiao, Jia Wei, Jiabing Wang, Qianli Ma, Shandian Zhe, Tolga Tasdizen
2020	A*	`conf`	Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations. AAAI Wei W. Xing, Shireen Y. Elhabian, Robert Michael Kirby, Ross T. Whitaker, Shandian Zhe
2020	J	`jnl`	Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications. CoRR Yun Yuan, Xianfeng Terry Yang, Zhao Zhang, Shandian Zhe
2020	A*	`conf`	Multi-Fidelity Bayesian Optimization via Deep Neural Networks. NeurIPS Shibo Li, Wei W. Xing, Robert M. Kirby, Shandian Zhe
2020	J	`jnl`	Multi-Fidelity Bayesian Optimization via Deep Neural Networks. CoRR Shibo Li, Wei W. Xing, Mike Kirby, Shandian Zhe
2020	J	`jnl`	Multi-Fidelity High-Order Gaussian Processes for Physical Simulation. CoRR Zheng Wang, Wei W. Xing, Robert Michael Kirby, Shandian Zhe
2020	A*	`conf`	Online Bayesian Sparse Learning with Spike and Slab Priors. ICDM Shikai Fang, Shandian Zhe, Kuang-Chih Lee, Kai Zhang, Jennifer Neville
2020	J	`jnl`	Physics Regularized Gaussian Processes. CoRR Zheng Wang, Wei W. Xing, Robert Michael Kirby, Shandian Zhe
2020	A*	`conf`	Probabilistic Neural-Kernel Tensor Decomposition. ICDM Conor Tillinghast, Shikai Fang, Kai Zhang, Shandian Zhe
2020	A*	`conf`	Scalable Gaussian Process Regression Networks. IJCAI Shibo Li, Wei W. Xing, Robert M. Kirby, Shandian Zhe
2020	A	`conf`	Scalable Nonparametric Factorization for High-Order Interaction Events. AISTATS Zhimeng Pan, Zheng Wang, Shandian Zhe
2020	J	`jnl`	Scalable Variational Gaussian Process Regression Networks. CoRR Shibo Li, Wei W. Xing, Mike Kirby, Shandian Zhe
2020	A*	`conf`	Self-Modulating Nonparametric Event-Tensor Factorization. ICML Zheng Wang, Xinqi Chu, Shandian Zhe
2020	—	`conf`	Semantic Tree-Based 3D Scene Model Recognition. MIPR Juefei Yuan, Tianyang Wang, Shandian Zhe, Yijuan Lu, Bo Li
2020	A	`conf`	Streaming Nonlinear Bayesian Tensor Decomposition. UAI Zhimeng Pan, Zheng Wang, Shandian Zhe
2020	J	`jnl`	Streaming Probabilistic Deep Tensor Factorization. CoRR Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe
2019	A	`conf`	Conditional Expectation Propagation. UAI Zheng Wang, Shandian Zhe
2019	J	`jnl`	Conditional Expectation Propagation. CoRR Zheng Wang, Shandian Zhe
2019	J	`jnl`	Deep Coregionalization for the Emulation of Spatial-Temporal Fields. CoRR Wei W. Xing, Robert M. Kirby, Shandian Zhe
2019	A	`conf`	Scalable High-Order Gaussian Process Regression. AISTATS Shandian Zhe, Wei W. Xing, Robert M. Kirby
2019	J	`jnl`	Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach. IEEE Trans. Neural Networks Learn. Syst. Liang Lan, Zhuang Wang, Shandian Zhe, Wei Cheng, Jun Wang, Kai Zhang
2019	J	`jnl`	Variational Random Function Model for Network Modeling. IEEE Trans. Neural Networks Learn. Syst. Zenglin Xu, Bin Liu, Shandian Zhe, Haoli Bai, Zihan Wang, Jennifer Neville
2018	—	`conf`	Data-driven resource flexing for network functions visualization. ANCS Lianjie Cao, Sonia Fahmy, Puneet Sharma, Shandian Zhe
2018	A*	`conf`	Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition. CVPR Jinmian Ye, Linnan Wang, Guangxi Li, Di Chen, Shandian Zhe, Xinqi Chu, Zenglin Xu
2018	J	`jnl`	NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition. Cogn. Comput. Bin Liu, Lirong He, Yingming Li, Shandian Zhe, Zenglin Xu
2018	A*	`conf`	Probabilistic Streaming Tensor Decomposition. ICDM Yishuai Du, Yimin Zheng, Kuang-Chih Lee, Shandian Zhe
2018	A*	`conf`	Stochastic Nonparametric Event-Tensor Decomposition. NeurIPS Shandian Zhe, Yishuai Du
2017	A*	`conf`	Asynchronous Distributed Variational Gaussian Process for Regression. ICML Hao Peng, Shandian Zhe, Xiao Zhang, Yuan Qi
2017	J	`jnl`	DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates. Bioinform. Hao Peng, Yifan Yang, Shandian Zhe, Jian Wang, Michael Gribskov, Yuan Qi
2017	J	`jnl`	Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition. CoRR Jinmian Ye, Linnan Wang, Guangxi Li, Di Chen, Shandian Zhe, Xinqi Chu, Zenglin Xu
2017	B	`conf`	Learning from semantically dependent multi-tasks. IJCNN Bin Liu, Zenglin Xu, Bo Dai, Haoli Bai, Xianghong Fang, Yazhou Ren, Shandian Zhe
2017	—	`—`	Scalable Bayesian Nonparametrics and Sparse Learning for Hidden Relationship Discovery Shandian Zhe
2017	A*	`conf`	Scalable Nonparametric Tensor Analysis. AAAI Shandian Zhe
2016	A*	`conf`	Annealed Sparsity via Adaptive and Dynamic Shrinking. KDD Kai Zhang, Shandian Zhe, Chaoran Cheng, Zhi Wei, Zhengzhang Chen, Haifeng Chen, Guofei Jiang, Yuan Qi, Jieping Ye
2016	J	`jnl`	Association Discovery and Diagnosis of Alzheimer's Disease with Bayesian Multiview Learning. J. Artif. Intell. Res. Zenglin Xu, Shandian Zhe, Yuan Qi, Peng Yu
2016	—	`conf`	Bayesian Group Feature Selection for Support Vector Learning Machines. PAKDD (1) Changde Du, Changying Du, Shandian Zhe, Ali Luo, Qing He, Guoping Long
2016	A*	`conf`	DinTucker: Scaling Up Gaussian Process Models on Large Multidimensional Arrays. AAAI Shandian Zhe, Yuan Qi, Youngja Park, Zenglin Xu, Ian M. Molloy, Suresh Chari
2016	—	`conf`	Distributed Flexible Nonlinear Tensor Factorization. NIPS Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-Chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani
2016	J	`jnl`	Distributed Flexible Nonlinear Tensor Factorization. CoRR Shandian Zhe, Pengyuan Wang, Kuang-Chih Lee, Zenglin Xu, Jian Yang, Youngja Park, Yuan Qi
2016	A*	`conf`	Fast Laplace Approximation for Sparse Bayesian Spike and Slab Models. IJCAI Syed Abbas Zilqurnain Naqvi, Shandian Zhe, Yuan Qi, Yifan Yang, Jieping Ye
2016	J	`jnl`	SWATShare - A web platform for collaborative research and education through online sharing, simulation and visualization of SWAT models. Environ. Model. Softw. Mohammad Adnan Rajib, Venkatesh M. Merwade, I Luk Kim, Lan Zhao, Carol X. Song, Shandian Zhe
2015	A*	`conf`	Bayesian Maximum Margin Principal Component Analysis. AAAI Changying Du, Shandian Zhe, Fuzhen Zhuang, Yuan Qi, Qing He, Zhongzhi Shi
2015	A	`conf`	Scalable Nonparametric Multiway Data Analysis. AISTATS Shandian Zhe, Zenglin Xu, Xinqi Chu, Yuan (Alan) Qi, Youngja Park
2015	A*	`conf`	Sparse Bayesian Multiview Learning for Simultaneous Association Discovery and Diagnosis of Alzheimer's Disease. AAAI Shandian Zhe, Zenglin Xu, Yuan Qi, Peng Yu
2014	Misc	`conf`	Joint Association Discovery and Diagnosis of Alzheimer's Disease by Supervised Heterogeneous Multiview Learning. Pacific Symposium on Biocomputing Shandian Zhe, Zenglin Xu, Yuan Qi, Peng Yu
2013	J	`jnl`	DinTucker: Scaling up Gaussian process models on multidimensional arrays with billions of elements. CoRR Shandian Zhe, Yuan Qi, Youngja Park, Ian M. Molloy, Suresh Chari
2013	J	`jnl`	Joint network and node selection for pathway-based genomic data analysis. Bioinform. Shandian Zhe, Syed A. Z. Naqvi, Yifan Yang, Yuan Qi
2013	J	`jnl`	Supervised Heterogeneous Multiview Learning for Joint Association Study and Disease Diagnosis CoRR Shandian Zhe, Zenglin Xu, Yuan Qi, Peng Yu
2011	J	`jnl`	Conditional Random Fields for Machine Translation System Combination. Int. J. Asian Lang. Process. Tian Xia, Shandian Zhe, Jinsong Su, Qun Liu
2010	—	`conf`	Conditional Random Fields for Machine Translation System Combination. IALP Tian Xia, Shandian Zhe, Qun Liu
2010	—	`conf`	Modeling Users' Information Goal Transitions and Satisfaction Judgment: Understanding the Full Search Process. Web Intelligence Shandian Zhe, Tian Xia, Xueqi Cheng