Shandian Zhe

According to our database1, Shandian Zhe authored at least 51 papers between 2010 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

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

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