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ORCIDHuiyan Sang
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2020 – today
- 2025
[i5]Stamatina Lamprinakou, Huiyan Sang, Bledar A. Konomi, Ligang Lu:
SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules. CoRR abs/2501.09900 (2025)- 2023
- [j7]Yan Zhong
, Huiyan Sang, Scott J. Cook, Paul M. Kellstedt:
Sparse spatially clustered coefficient model via adaptive regularization. Comput. Stat. Data Anal. 177: 107581 (2023) - [c8]Jian Cao, Myeongjong Kang, Felix Jimenez, Huiyan Sang, Florian Tobias Schaefer, Matthias Katzfuss:
Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization. ICML 2023: 3559-3576 - [i4]Jian Cao, Myeongjong Kang, Felix Jimenez, Huiyan Sang, Florian Schäfer, Matthias Katzfuss:
Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization. CoRR abs/2301.13303 (2023) - 2022
- [j6]Bohai Zhang, Furong Li, Huiyan Sang, Noel Cressie:
Inferring Changes in Arctic Sea Ice through a Spatio-Temporal Logistic Autoregression Fitted to Remote-Sensing Data. Remote. Sens. 14(23): 5995 (2022) - [c7]Changwoo J. Lee, Huiyan Sang:
Why the Rich Get Richer? On the Balancedness of Random Partition Models. ICML 2022: 12521-12541 - [c6]Zhao Tang Luo, Huiyan Sang, Bani K. Mallick:
BAMDT: Bayesian Additive Semi-Multivariate Decision Trees for Nonparametric Regression. ICML 2022: 14509-14526 - [c5]Hyunwoong Chang, Changwoo J. Lee, Zhao Tang Luo, Huiyan Sang, Quan Zhou:
Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems. NeurIPS 2022 - [i3]Changwoo J. Lee, Huiyan Sang:
Why the Rich Get Richer? On the Balancedness of Random Partition Models. CoRR abs/2201.12697 (2022) - 2021
- [j5]Zhao Tang Luo, Huiyan Sang, Bani K. Mallick:
A Bayesian Contiguous Partitioning Method for Learning Clustered Latent Variables. J. Mach. Learn. Res. 22: 37:1-37:52 (2021) - [c4]Zhao Tang Luo, Huiyan Sang, Bani K. Mallick:
BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained Domain. NeurIPS 2021: 90-102 - [c3]Changwoo J. Lee, Zhao Tang Luo, Huiyan Sang:
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs. NeurIPS 2021: 598-609 - [c2]Lihao Yin, Ganggang Xu, Huiyan Sang, Yongtao Guan:
Row-clustering of a Point Process-valued Matrix. NeurIPS 2021: 20028-20039 - [i2]Lihao Yin, Ganggang Xu, Huiyan Sang, Yongtao Guan:
Row-clustering of a Point Process-valued Matrix. CoRR abs/2110.01207 (2021)
2010 – 2019
- 2017
- [j4]Weijia Han, Huiyan Sang, Xiao Ma, Jiandong Li, Yanyan Zhang, Shuguang Cui:
Sensing Statistical Primary Network Patterns via Bayesian Network Structure Learning. IEEE Trans. Veh. Technol. 66(4): 3143-3157 (2017) - 2015
- [j3]Bohai Zhang, Bledar A. Konomi, Huiyan Sang, Georgios Karagiannis, Guang Lin:
Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions. J. Comput. Phys. 300: 623-642 (2015) - [j2]Avishek Chakraborty, Swarup De, Kenneth P. Bowman, Huiyan Sang, Marc G. Genton, Bani K. Mallick:
An adaptive spatial model for precipitation data from multiple satellites over large regions. Stat. Comput. 25(2): 389-405 (2015) - [c1]Weijia Han, Huiyan Sang, Min Sheng, Jiandong Li, Shuguang Cui:
Efficient learning of statistical primary patterns via Bayesian network. ICC 2015: 4871-4876 - 2014
- [i1]Weijia Han, Huiyan Sang, Min Sheng, Jiandong Li, Shuguang Cui:
Cognitive Learning of Statistical Primary Patterns via Bayesian Network. CoRR abs/1409.7930 (2014)
2000 – 2009
- 2009
- [j1]Andrew O. Finley, Huiyan Sang, Sudipto Banerjee, Alan E. Gelfand:
Improving the performance of predictive process modeling for large datasets. Comput. Stat. Data Anal. 53(8): 2873-2884 (2009)
Coauthor Index
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