Yang Ni

发表

Polygenic prediction via Bayesian regression and continuous shrinkage priors

Yang Ni, Tian Ge, Chia-Yen Chen, 2018, Nature Communications.

Bayesian Hierarchical Varying-Sparsity Regression Models with Application to Cancer Proteogenomics

Yang Ni, R. Akbani, V. Baladandayuthapani, 2018, Journal of the American Statistical Association.

Bayesian biclustering for microbial metagenomic sequencing data via multinomial matrix factorization.

Yang Ni, Qiwei Li, R. Chapkin, 2020, Biostatistics.

Integrative Bayesian Network Analysis of Genomic Data

Yang Ni, V. Baladandayuthapani, F. Stingo, 2014, Cancer informatics.

Bayesian Graphical Regression

Yang Ni, Veerabhadran Baladandayuthapani, Francesco C. Stingo, 2018, Journal of the American Statistical Association.

BAGEL: A BAYESIAN GRAPHICAL MODEL FOR INFERRING DRUG EFFECT LONGITUDINALLY ON DEPRESSION IN PEOPLE WITH HIV.

Yang Ni, Yanxun Xu, L. Rubin, 2020, The annals of applied statistics.

Sparse Multi-Dimensional Graphical Models: A Unified Bayesian Framework

Yang Ni, Veerabhadran Baladandayuthapani, Francesco C. Stingo, 2017 .

TEAMS: Toxicity- and Efficacy-Based Dose-Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology

Yang Ni, Wentian Guo, Yuan Ji, 2015, Statistics in biosciences.

Variance in estimated pairwise genetic distance under high versus low coverage sequencing: The contribution of linkage disequilibrium.

Yang Ni, M. Shpak, Jie Lu, 2017, Theoretical population biology.

Variance in Estimated Pairwise Genetic Distance Under High versus Low Coverage Sequencing: the Contribution of Linkage Disequilibrium

Yang Ni, M. Shpak, Peter R. Mueller, 2017 .

A Unified Bayesian Framework for Bi-overlapping-Clustering Multi-omics Data via Sparse Matrix Factorization

James J. Cai, Yang Ni, L. Davidson, 2022, Statistics in Biosciences.

Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation

Yang Ni, 2022, 2209.08579.

Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure

Yang Ni, V. Baladandayuthapani, F. Stingo, 2022, J. Mach. Learn. Res..

Individualized Inference using Bayesian Quantile Directed Acyclic Graphical Models

Yang Ni, V. Baladandayuthapani, A. Bhadra, 2022 .

Supplementary Material for “Bayesian Graphical Regression”

Yang Ni, F. Stingo, Baladandayuthapani, 2017 .

Sparse semiparametric discriminant analysis for high-dimensional zero-inflated data

Hee Cheol Chung, Yang Ni, Irina Gaynanova, 2022, 2208.03734.

Functional Bayesian networks for discovering causality from multivariate functional data

Yang Ni, Yanxun Xu, Fangting Zhou, 2022, Biometrics.

Ordinal causal discovery

B. Mallick, Yang Ni, 2022, UAI.

Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation

Yang Ni, 2022, NeurIPS.

Federated Learning for Sparse Bayesian Models with Applications to Electronic Health Records and Genomics

Yang Ni, Yanxun Xu, Kunbo Wang, 2022, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

Scalable Bayesian Nonparametric Clustering and Classification

Yang Ni, Yuan Ji, Yitan Zhu, 2018, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

Polygenic prediction via Bayesian regression and continuous shrinkage priors

T. Ge, Chia-Yen Chen, Yang Ni, 2018, bioRxiv.

Estimation of Pairwise Genetic Distances Under Independent Sampling of Segregating Sites vs. Haplotype Sampling

Yang Ni, M. Shpak, Peter R. Mueller, 2017, bioRxiv.

Bayesian nonlinear model selection for gene regulatory networks

Francesco C Stingo, Yang Ni, Veerabhadran Baladandayuthapani, 2015, Biometrics.

Phylogenetically informed Bayesian truncated copula graphical models for microbial association networks

Yang Ni, Irina Gaynanova, Hee Cheol Chung, 2021, The Annals of Applied Statistics.

Consensus Monte Carlo for Random Subsets Using Shared Anchors

Yuan Ji, Yang Ni, Peter Mueller, 2019, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

Supplementary Material of "Bayesian Causal Structural Learning with Zero-Inﬂated Poisson Bayesian Networks"

Junsouk Choi, Robert S. Chapkin, Yang Ni, 2020 .

Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior

Raymond K. W. Wong, Yang Ni, Kejun He, 2023, Technometrics.

Bayesian Double Feature Allocation for Phenotyping With Electronic Health Records

Yuan Ji, Yang Ni, Peter Mueller, 2018, Journal of the American Statistical Association.

Heterogeneous reciprocal graphical models

Yang Ni, Peter Müller, Yuan Ji, 2016, Biometrics.

Bayesian graphical models for modern biological applications

Marina Vannucci, Yang Ni, Veerabhadran Baladandayuthapani, 2021, Statistical Methods & Applications.

A Bayesian nonparametric approach for inferring drug combination effects on mental health in people with HIV

Yang Ni, Yanxun Xu, Leah H Rubin, 2020, Biometrics.

Bayesian Covariate-Dependent Quantile Directed Acyclic Graphical Models for Individualized Inference

Yang Ni, V. Baladandayuthapani, A. Bhadra, 2022, 2210.08096.

Bayesian graphical models for computational network biology

Yuan Ji, Yang Ni, Lin Wei, 2017, BMC Bioinformatics.

Reciprocal Graphical Models for Integrative Gene Regulatory Network Analysis

Yuan Ji, Yang Ni, Peter Mueller, 2016, Bayesian Analysis.

Handbook of Bayesian Variable Selection

Yang Ni, 2023 .

PHYLOGENETICALLY INFORMED BAYESIAN TRUNCATED COPULA GRAPHICAL MODELS FOR MICROBIAL ASSOCIATION NETWORKS BY HEE

Hee Cheol Chung, Yang Ni, Irina Gaynanova, 2021 .

Blocked Gibbs sampler for hierarchical Dirichlet processes

B. Mallick, D. Pati, Yang Ni, 2023, 2304.09945.

Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data

B. Mallick, Yang Ni, R. Chapkin, 2023, 2302.09111.

Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data.

B. Mallick, D. Pati, Yang Ni, 2023, Journal of the American Statistical Association.

Bayesian approaches for large biological networks

Yang Ni, Veerabhadran Baladandayuthapani, Giovanni M. Marchetti, 2015 .

Causal discovery with heterogeneous observational data

Yang Ni, Fangting Zhou, Kejun He, 2022, UAI.

Model-based Causal Discovery for Zero-Inflated Count Data

Yang Ni, Junsouk Choi, 2023, J. Mach. Learn. Res..

Bayesian graphical models for computational network biology

Yuan Ji, Yang Ni, Lin Wei, 2017, BMC Bioinformatics.

Individualized causal discovery with latent trajectory embedded Bayesian networks

Yang Ni, Fangting Zhou, Kejun He, 2023, Biometrics.

Parallel-Tempered Feature Allocation for Large-Scale Tumor Heterogeneity with Deep Sequencing Data

Peter Müller, Yang Ni, Yuan Ji, 2016, Springer Proceedings in Mathematics & Statistics.

Supplementary Material of "Bayesian Causal Structural Learning with Zero-Inﬂated Poisson Bayesian Networks"

Yang Ni, R. Chapkin, Junsouk Choi, 2020 .

Bayesian biclustering for microbial metagenomic sequencing data via multinomial matrix factorization.

Yang Ni, Robert S Chapkin, Qiwei Li, 2020, Biostatistics.