Publications

(2023). Functional Bayesian Networks for Discovering Causality from Multivariate Functional Data. Biometrics, just accepted.

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(2023). Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data. Journal of the American Statistical Association, just accepted.

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(2023). Graphical Dirichlet Process. arXiv:2302.09111.

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(2023). A Bayesian Decision Framework for Optimizing Sequential Combination Antiretroviral Therapy in People with HIV. Annals of Applied Statistics, just accepted.

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(2023). Individualized Causal Discovery with Latent Trajectory Embedded Bayesian Networks. Biometrics, just accepted.

(2023). Model-Based Causal Discovery for Zero-Inflated Count Data. Journal of Machine Learning Research, just accepted.

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(2023). Federated Learning for Sparse Bayesian Models with Applications to Electronic Health Records and Genomics. Pacific Symposium on Biocomputing 2023.

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(2023). Multi-Way Overlapping Clustering by Bayesian Tensor Decomposition. Statistics and Its Interface, just accepted.

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(2023). Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior. Technometrics, accepted subject to minor revision.

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

(2022). Individualized Inference in Bayesian Quantile Directed Acyclic Graphical Models. arXiv:2210.08096.

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

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

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(2022). Bayesian Hierarchical Quantile Regression with Application to Characterizing the Immune Architecture of Lung Cancer. Biometrics, just accepted.

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(2022). Sparse Semiparametric Discriminant Analysis for High-Dimensional Zero-Inflated Data. arXiv:2208.03734.

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(2022). A Unified Bayesian Framework for Bi-Overlapping-Clustering Multi-Omics Data via Sparse Matrix Factorization. Statistics in Biosciences, just accepted.

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

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

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(2022). Phylogenetically Informed Bayesian Truncated Copula Graphical Models for Microbial Association Networks. Annals of Applied Statistics, 16(4), 2437-2457.

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(2022). Rejoinder to the Discussion of "Bayesian Graphical Models for Modern Biological Applications.". Statistical Methods and Applications.

(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.

(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.

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(2021). DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. IEEE Transactions on Neural Networks and Learning Systems, 1-11.

(2021). Bayesian Graphical Models for Modern Biological Applications. Statistical Methods and Applications (with Discussion).

(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].

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(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].

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(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%)].

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(2020). Consensus Variational and Monte Carlo Algorithms for Bayesian Nonparametric Clustering. 2020 IEEE International Conference on Big Data.

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

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

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(2020). Adversarial Domain Adaptation Being Aware of Class Relationships. The 24th European Conference on Artificial Intelligence.

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(2020). Scalable Bayesian Nonparametric Clustering and Classification. Journal of Computational and Graphical Statistics, 29(1), 53-65.

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(2020). Heterogeneity of Human Prostate Carcinoma-Associated Fibroblasts Implicates a Role for Subpopulations in Myeloid Cell Recruitment. Prostate, 80(2), 173-185.

(2019). Bayesian Hierarchical Varying-sparsity Model with Application to Cancer Proteogenomics. Journal of the American Statistical Association (Applications & Case Studies), 114(525), 184-197.

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(2019). Polygenic Prediction via Bayesian Regression and Continuous Shrinkage Priors. Nature Communications, 10(1), 1776.
[Selected as Editors’ Highlights].

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(2019). Bayesian Graphical Regression. Journal of the American Statistical Association (Theory & Methods), 114(525), 48-60.

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(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.

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(2018). Heterogeneous Reciprocal Graphical Models. Biometrics, 74(2), 606-615.

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(2018). Reciprocal Graphical Models for Integrative Gene Regulatory Network Analysis. Bayesian Analysis, 13(4), 1095–1110.

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(2018). Bayesian Graphical Models for Computational Network Biology. BMC Bioinformatics, 19(3), 63.

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

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(2017). Variance in Estimated Pairwise Genetic Distance Under High versus Low Coverage Sequencing: the Contribution of Linkage Disequilibrium. Theoretical Population Biology, 117, 51-63.

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

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(2015). Bayesian Nonlinear Model Selection for Gene Regulatory Networks. Biometrics, 71(3), 585-595.

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(2015). Bayesian Approaches for Large Biological Networks. In Nonparametric Bayesian Methods in Biostatistics and Bioinformatics, Mitra, R. and Müller, P. (eds), Springer-Verlag.

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(2014). Integrative Bayesian Network Analysis of Genomic Data. Cancer Informatics, 13(s2), 39-48.

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