Bayesian Nonparametrics

Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data

Graphical Dirichlet process.

Blocked Gibbs Sampler for Hierarchical Dirichlet Processes

Posterior computation in hierarchical Dirichlet process (HDP) mixture models is an active area of research in nonparametric Bayes inference of grouped data. Existing literature almost exclusively focuses on the Chinese restaurant franchise (CRF) …

A Bayesian Approach for Investigating the Pharmacogenetics of Combination Antiretroviral Therapy in People with HIV

Pharmacogenetics of cART in HIV

Multi-Way Overlapping Clustering by Bayesian Tensor Decomposition

Bayesian multi-way clustering.

Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data

A new Gaussian graphical model that produces subject-specific and predictive graphs with theoretical guarantee.

A Unified Bayesian Framework for Bi-Overlapping-Clustering Multi-Omics Data via Sparse Matrix Factorization

Bayesian integrative matrix factorization.

BAGEL: A Bayesian Graphical Model for Inferring Drug Effect on Depression Longitudinally in People with HIV

HIV Longitudinal Drug Effects on Mental Health

DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering

Deep Nonparametric Bayes Clustering

A Bayesian Nonparametric Approach for Inferring Drug Combination Effects on Mental Health in People with HIV

HIV Drug Combination Effects on Mental Health

Bayesian Biclustering for Microbial Metagenomic Sequencing Data via Multinomial Matrix Factorization

Bayesian biclustering via multinomial matrix factorization.

Consensus Variational and Monte Carlo Algorithms for Bayesian Nonparametric Clustering

Consensus variational inference.

Consensus Monte Carlo for Random Subsets using Shared Anchors

Consensus Monte Carlo algorithm for DP and IBP

Bayesian Double Feature Allocation for Phenotyping with Electronic Health Records

A categorical matrix factorization method to infer latent diseases from EHR data.

Scalable Bayesian Nonparametric Clustering and Classification

A scalable Monte Carlo algorithm for inference under a large class of nonparametric Bayesian models for clustering and classification.

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

We develop a parallel-tempered feature allocation algorithm to infer tumor heterogeneity from deep DNA sequencing data. The feature allocation model is based on a binomial likelihood and an Indian Buffet process prior on the latent haplotypes. A …

Heterogeneous Reciprocal Graphical Models

A hierarchical reciprocal graphical models to infer gene networks from heterogeneous data with or without known groups.