ProfessorsProfessors of University of California, Los AngelesQing Zhou

Qing Zhou

University of California, Los Angeles

H-index: 27

North America-United States

About Qing Zhou

Qing Zhou, With an exceptional h-index of 27 and a recent h-index of 18 (since 2020), a distinguished researcher at University of California, Los Angeles, specializes in the field of Graphical Models, Causal Inference, Monte Carlo Methods, Bioinformatics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Federated Learning of Generalized Linear Causal Networks

Structure learning of latent factors via clique search on correlation thresholded graphs

Bayesian Causal Bandits with Backdoor Adjustment Prior

An empirical Bayes approach to stochastic blockmodels and graphons: shrinkage estimation and model selection

A non-graphical representation of conditional independence via the neighbourhood lattice

On perfectness in Gaussian graphical models

Partitioned hybrid learning of Bayesian network structures

Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores

Qing Zhou Information

University	University of California, Los Angeles
Position	Professor of Statistics
Citations(all)	6375
Citations(since 2020)	3002
Cited By	4500
hIndex(all)	27
hIndex(since 2020)	18
i10Index(all)	40
i10Index(since 2020)	27
Email	Access Email
University Profile Page	University of California, Los Angeles
Google Scholar	View Google Scholar Profile

Qing Zhou Skills & Research Interests

Graphical Models

Causal Inference

Monte Carlo Methods

Bioinformatics

Top articles of Qing Zhou

Title	Journal	Author(s)	Publication Date
Federated Learning of Generalized Linear Causal Networks	IEEE Transactions on Pattern Analysis and Machine Intelligence	Qiaoling Ye Arash A Amini Qing Zhou	2024/3/26
Structure learning of latent factors via clique search on correlation thresholded graphs		Dale Kim Qing Zhou	2023/7/3
Bayesian Causal Bandits with Backdoor Adjustment Prior	Transactions on Machine Learning Research	Jireh Huang Qing Zhou	2023/1/31
An empirical Bayes approach to stochastic blockmodels and graphons: shrinkage estimation and model selection	PeerJ Computer Science	Zhanhao Peng Qing Zhou	2022/7/6
A non-graphical representation of conditional independence via the neighbourhood lattice	arXiv preprint arXiv:2206.05829	Arash A Amini Bryon Aragam Qing Zhou	2022/6/12
On perfectness in Gaussian graphical models		Arash Amini Bryon Aragam Qing Zhou	2022/5/3
Partitioned hybrid learning of Bayesian network structures	Machine Learning	Jireh Huang Qing Zhou	2022/3/16
Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores	Transactions on Machine Learning Research	Gabriel Ruiz OSCAR HERNAN MADRID PADILLA Qing Zhou	2022/12
Causal network learning with non-invertible functional relationships	Computational Statistics & Data Analysis	Bingling Wang Qing Zhou	2021/4/1
Honest confidence sets for high-dimensional regression by projection and shrinkage	Journal of the American Statistical Association	Kun Zhou Ker-Chau Li Qing Zhou	2021/7/21
A Bayesian hierarchical model for estimating the statistical parameters in a three-parameter log-normal distribution for monthly average streamflows	Journal of Hydrology	Jinshu Li Qing Zhou William W-G Yeh	2020/12/1
Statistical inference of differential RNA-editing sites from RNA-sequencing data by hierarchical modeling	Bioinformatics	Stephen S Tran Qing Zhou Xinshu Xiao	2020/5/1
Optimizing regularized cholesky score for order-based learning of bayesian networks	IEEE transactions on pattern analysis and machine intelligence	Qiaoling Ye Arash A Amini Qing Zhou	2020/4/27
Learning Big Gaussian Bayesian Networks: Partition, Estimation and Fusion	Journal of Machine Learning Research	Jiaying Gu Qing Zhou	2020