Publications

Yang Ni, Su Chen, Zeya Wang (2024). Casual Structural Modeling of Survey Questionnaires via a Bootstrapped Ordinal Bayesian Network Approach. Psychometrika, just accepted.

Arhit Chakrabarti, Yang Ni, Ellen Ruth A. Morris, Michael L. Salinas, Robert S. Chapkin, Bani K. Mallick (2024). Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data. Journal of Machine Learning Research, just accepted.
[Student Paper Award Winner of the Section on Bayesian Statistical Science (SBSS) of the ASA].

Wei Jin, Yang Ni, Amanda B. Spence, Leah H. Rubin, Yanxun Xu (2024). Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Time-Series Data. Journal of Machine Learning Research, minor revision.

Snigdha Das, Yabo Niu, Yang Ni, Bani K. Mallick, Debdeep Pati (2024). Blocked Gibbs Sampler for Hierarchical Dirichlet Processes. Journal of Computational and Graphical Statistics, just accepted.

Arhit Chakrabarti, Yang Ni, Bani K. Mallick (2024). Joint Bayesian Estimation of Cell Dependence and Gene Associations in Spatially Resolved Transcriptomic Data. Scientific Reports, 14(1), 9516.

Canaan M. Whitfeld‑Cargile, Hee Cheol Chung, M. C. Coleman, N. D. Cohen, A. M. Chamoun‑Emanuelli, Ivan Ivanov, J. S. Goldsby, Laurie A. Davidson, Irina Gaynanova, Yang Ni, Robert S. Chapkin (2024). Integrated Analysis of Gut Metabolome, Microbiome, and Exfoliome Data in an Equine Model of Intestinal Injury. Microbiome, 12, 74.

Wei Jin, Yang Ni, Amanda B. Spence, Leah H. Rubin, Yanxun Xu (2024). A Bayesian Approach for Investigating the Pharmacogenetics of Combination Antiretroviral Therapy in People with HIV. Biostatistics, just accepted.

Zhuofan Wang, Fangting Zhou, Kejun He, Yang Ni (2024). Multi-Way Overlapping Clustering by Bayesian Tensor Decomposition. Statistics and Its Interface, 17, 219–230.

Yang Ni (2024). Deep Learning and Scientific Computing with R torch by Sigrid Keydana. The American Statistician.

Saptarshi Roy, Raymond K. W. Wong, Yang Ni (2023). Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data. Advances in Neural Information Processing Systems (NeurIPS) 36.
[Recipient of Scholar Award from NeurIPS].

Fangting Zhou, Kejun He, Kunbo Wang, Yanxun Xu, Yang Ni (2023). Functional Bayesian Networks for Discovering Causality from Multivariate Functional Data. Biometrics, 79, 3279–3293.

Yabo Niu, Yang Ni, Debdeep Pati, Bani K. Mallick (2023). Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data. Journal of the American Statistical Association, just accepted.

Fangting Zhou, Kejun He, Yang Ni (2023). Individualized Causal Discovery with Latent Trajectory Embedded Bayesian Networks. Biometrics, 79(4), 3191-3202.

Junsouk Choi, Yang Ni (2023). Model-Based Causal Discovery for Zero-Inflated Count Data. Journal of Machine Learning Research, 24(200), 1-32.

Shuoli Chen, Kejun He, Shiyuan He, Yang Ni, Raymond K.W. Wong (2023). Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior. Technometrics, 65(4), 524–536.

Yang Ni (2023). Handbook of Bayesian Variable Selection by Mahlet G. Tadesse and Marina Vannucci. Journal of the American Statistical Association.

Ksheera Sagar, Yang Ni, Veerabhadran Baladandayuthapani, Anindya Bhadra (2022). Individualized Inference in Bayesian Quantile Directed Acyclic Graphical Models. arXiv:2210.08096.

Yang Ni (2022). Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation. Advances in Neural Information Processing Systems (NeurIPS) 35.

Yang Ni, Francesco Stingo, Veerabhadran Baladandayuthapani (2022). Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure. Journal of Machine Learning Research, 23(242), 1-29.

Priyam Das, Christine B. Peterson, Yang Ni, Alexandre Reuben, Jiexin Zhang, Jianjun Zhang, Kim-Anh Do, Veerabhadran Baladandayuthapani (2022). Bayesian Hierarchical Quantile Regression with Application to Characterizing the Immune Architecture of Lung Cancer. Biometrics, just accepted.

Hee Cheol Chung, Yang Ni, Irina Gaynanova (2022). Sparse Semiparametric Discriminant Analysis for High-Dimensional Zero-Inflated Data. arXiv:2208.03734.

Fangting Zhou, Kejun He, James J. Cai, Laurie A. Davidson, Robert S. Chapkin, Yang Ni (2022). A Unified Bayesian Framework for Bi-Overlapping-Clustering Multi-Omics Data via Sparse Matrix Factorization. Statistics in Biosciences, just accepted.

Fangting Zhou, Kejun He, Yang Ni (2022). Causal Discovery with Heterogeneous Observational Data. Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 180:2383-2393.

Yang Ni, Bani Mallick (2022). Ordinal Causal Discovery. Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 180:1530-1540.

Hee Cheol Chung, Irina Gaynanova, Yang Ni (2022). Phylogenetically Informed Bayesian Truncated Copula Graphical Models for Microbial Association Networks. Annals of Applied Statistics, 16(4), 2437-2457.

Yang Ni, Veerabhadran Baladandayuthapani, Marina Vannucci, Francesco C. Stingo (2022). Rejoinder to the Discussion of "Bayesian Graphical Models for Modern Biological Applications.". Statistical Methods and Applications.

Yang Ni (2022). Exploratory Data Analysis with MATLAB (Third Edition) by Wendy L. Martinez, Angel R. Martinez, and Jeffrey L. Solka. The American Statistician, 76(1), 85-86.

Yang Ni (2022). Bayesian Thinking in Biostatistics by Gary L. Rosner, Purushottam W. Laud, and Wesley O. Johnson. Journal of the American Statistical Association, 117(538), 1041-1042.

Yuliang Li, Yang Ni, Leah H. Rubin, Amanda B. Spence, Yanxun Xu (2021). BAGEL: A Bayesian Graphical Model for Inferring Drug Effect on Depression Longitudinally in People with HIV. Annals of Applied Statistics, 16(1), 21–39.

Zeya Wang, Yang Ni, Baoyu Jing, Deqing Wang, Hao Zhang, Eric Xing (2021). DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. IEEE Transactions on Neural Networks and Learning Systems, 1-11.

Yang Ni, Veerabhadran Baladandayuthapani, Marina Vannucci, Francesco C. Stingo (2021). Bayesian Graphical Models for Modern Biological Applications. Statistical Methods and Applications (with Discussion).

Wei Jin, Yang Ni, Leah H. Rubin, Amanda B. Spence, Yanxun Xu (2021). A Bayesian Nonparametric Approach for Inferring Drug Combination Effects on Mental Health in People with HIV. Biometrics, 78, 988–1000.
[Student Paper Award Winner of the Mental Health Statistics Section (MHSS) of the ASA].

Fangting Zhou, Kejun He, Qiwei Li, Robert S. Chapkin, Yang Ni (2021). Bayesian Biclustering for Microbial Metagenomic Sequencing Data via Multinomial Matrix Factorization. Biostatistics, 23(3), 891–909.
[Student Paper Award Winner of the Section on Bayesian Statistical Science (SBSS) of the ASA].

Junsouk Choi, Robert S. Chapkin, Yang Ni (2020). Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks. Advances in Neural Information Processing Systems (NeurIPS) 33.
[Spotlight Presentation (385 out of 9454, acceptance rate 4%)].

Yang Ni, David Jones, Zeya Wang (2020). Consensus Variational and Monte Carlo Algorithms for Bayesian Nonparametric Clustering. 2020 IEEE International Conference on Big Data.

Yang Ni, Yuan Ji, Peter Müller (2020). Consensus Monte Carlo for Random Subsets using Shared Anchors. Journal of Computational and Graphical Statistics, 29(4), 703-714.

Yang Ni, Peter Müller, Yuan Ji (2020). Bayesian Double Feature Allocation for Phenotyping with Electronic Health Records. Journal of the American Statistical Association (Applications & Case Studies), 115(532), 1620-1634.

Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric Xing (2020). Adversarial Domain Adaptation Being Aware of Class Relationships. The 24th European Conference on Artificial Intelligence.

Yang Ni, Peter Müller, Maurice Diesendruck, Sinead Williamson, Yitan Zhu, Yuan Ji (2020). Scalable Bayesian Nonparametric Clustering and Classification. Journal of Computational and Graphical Statistics, 29(1), 53-65.

Renee E. Vickman, Meaghan M. Broman, Nadia A. Lanman, Omar E. Franco, Putu Ayu G. Sudyanti, Yang Ni, Yuan Ji, Brian T. Helfand, Jacqueline Petkewicz, Michael Paterakos, Susan E. Crawford, Timothy L. Ratliff, Simon W. Hayward (2020). Heterogeneity of Human Prostate Carcinoma-Associated Fibroblasts Implicates a Role for Subpopulations in Myeloid Cell Recruitment. Prostate, 80(2), 173-185.

Yang Ni, Francesco Stingo, Min Jin Ha, Rehan Akbani, Veerabhadran Baladandayuthapani (2019). Bayesian Hierarchical Varying-sparsity Model with Application to Cancer Proteogenomics. Journal of the American Statistical Association (Applications & Case Studies), 114(525), 184-197.

Tian Ge, Chia-Yen Chen, Yang Ni, Yen-Chen Anne Feng, Jordan W. Smoller (2019). Polygenic Prediction via Bayesian Regression and Continuous Shrinkage Priors. Nature Communications, 10(1), 1776.
[Selected as Editors’ Highlights].

Yang Ni, Francesco Stingo, Veerabhadran Baladandayuthapani (2019). Bayesian Graphical Regression. Journal of the American Statistical Association (Theory & Methods), 114(525), 48-60.

Yang Ni, Peter Müller, Max Shpak, Yuan Ji (2019). Parallel-Tempered Feature Allocation for Large-Scale Tumor Heterogeneity with Deep Sequencing Data. In Liu R., Tsong Y. (eds) Pharmaceutical Statistics. MBSW 2016. Springer Proceedings in Mathematics & Statistics, vol 218. Springer, Cham.

Yang Ni, Peter Müller, Yitan Zhu, Yuan Ji (2018). Heterogeneous Reciprocal Graphical Models. Biometrics, 74(2), 606-615.

Yang Ni, Peter Müller, Yuan Ji (2018). Reciprocal Graphical Models for Integrative Gene Regulatory Network Analysis. Bayesian Analysis, 13(4), 1095–1110.

Yang Ni, Peter Müller, Wei Lin, Yuan Ji (2018). Bayesian Graphical Models for Computational Network Biology. BMC Bioinformatics, 19(3), 63.

Yang Ni, Francesco Stingo, Veerabhadran Baladandayuthapani (2017). Sparse Multi-Dimensional Graphical Models: A Unified Bayesian Framework. Journal of the American Statistical Association (Theory & Methods), 112(518), 779-793.

Max Shpak, Yang Ni, Jie Lu, Peter Müller (2017). Variance in Estimated Pairwise Genetic Distance Under High versus Low Coverage Sequencing: the Contribution of Linkage Disequilibrium. Theoretical Population Biology, 117, 51-63.

Yang Ni, Peter Müller (2017). Discussion of "Sparse Graphs Using Exchangeable Random Measures." by Caron, F., and Fox, E.. Journal of the Royal Statistical Society: Series B.

Yang Ni, Francesco Stingo, Veerabhadran Baladandayuthapani (2015). Bayesian Nonlinear Model Selection for Gene Regulatory Networks. Biometrics, 71(3), 585-595.

Yang Ni, Giovanni Marchetti, Veerabhadran Baladandayuthapani, Francesco Stingo (2015). Bayesian Approaches for Large Biological Networks. In Nonparametric Bayesian Methods in Biostatistics and Bioinformatics, Mitra, R. and Müller, P. (eds), Springer-Verlag.

Yang Ni, Francesco Stingo, Veerabhadran Baladandayuthapani (2014). Integrative Bayesian Network Analysis of Genomic Data. Cancer Informatics, 13(s2), 39-48.