SPEED 4: Bayesian Analysis and Computational Methods, Part 1 -- JSM 2025

A general framework for probabilistic model uncertainty

10:35 AM - 10:40 AM

Co-authors: Vik Shirvaikar (University of Oxford), Chris Holmes (University of Oxford), Vik Shirvaikar (University of Oxford), Stephen Walker

predictive inference model uncertainty hypothesis testing

A Scaling Neural Network-Based Approach for Variable Selection in Nonparametric Regression

10:40 AM - 10:45 AM

Co-authors: Jiuchen Zhang (University of California, Irvine), Ling Zhou, Jiuchen Zhang (University of California, Irvine), Peter Song (University of Michigan)

Variable Selection Neural Network Nonparametric Environmental Science

Bayesian Deep Gaussian Processes for Correlated Functional Data: A Case Study in Power Spectra

10:45 AM - 10:50 AM

Co-authors: Stephen Walsh (Elms College), Stephen Walsh (Elms College), Annie Booth (Virginia Tech), David Higdon (Virginia Tech), Marco Ferreira (Virginia Tech)

Deep Gaussian Processes Hierarchical Modeling Cosmology Markov Chain Monte Carlo Surrogate Uncertainty Quanitification

Bayesian Estimation of Population Average Causal Effects from a Collection of Trials

10:50 AM - 10:55 AM

Co-authors: Patrick McHugh, Christopher Hans (The Ohio State University), Patrick McHugh, Eloise Kaizar (The Ohio State University)

meta analysis generalizability mixed effects models

Bayesian latent class analysis with sparse finite mixtures

10:55 AM - 11:00 AM

Co-authors: Deborah Kunkel (Clemson University), Erica Porter (Clemson University), Erica Porter (Clemson University)

Latent class analysis Bayesian mixture model Cluster analysis

Bayesian Magnitude and Phase Estimation of k-Space Data Enhances Reconstructed Image Quality

11:00 AM - 11:05 AM

Co-authors: John Bodenschatz, Dan Rowe (Marquette University), John Bodenschatz

Bayesian fMRI k-space

Bayesian Semiparametric Estimation of Optimal Treatment Regimes with Irregularly Observed Data

11:05 AM - 11:10 AM

Co-authors: Larry Dong, Larry Dong, Eleanor Pullenayegum (Hospital for Sick Children), Olli Saarela (University of Toronto)

Dynamic treatment regimes irregularly observed data inverse weighting Bayesian semiparametric estimation statistical precision medicine

Bayesian Small Area Estimation of Proportions Using Archimedean Copula Models with Random Effects

11:10 AM - 11:15 AM

Co-authors: Fode Tounkara, Fode Tounkara

Small Area Estimation Bayesian Inference Archimedean Copulas, Random Effects Empirical Best Predictor (EBP)Maximum Likelihood Estimation Jackknife Method

WITHDRAWN Eliciting some generalisations of Dirichlet distribution as priors for Multinomial models

11:20 AM - 11:25 AM

Co-authors: Nayana Unnipillai, Fadlalla Elfadaly (The Open University, Walton Hall, Milton Keynes, UK)

Bayesian Statistics Prior Elicitation Expert Elicitation Dirichlet Distribution Shiny R

From Naive Bayes to Large Language Models: A New Era of Text-Based Classification

11:30 AM - 11:35 AM

Co-authors: Abdul Wasay (Autodesk), Abdul Wasay (Autodesk), Rajat Verma

Text classification Large language models (LLMs)Transformer architectures BERT Cost-effective solutions Modern text analytics

Generalized Bayesian Inference for Dynamic Random Dot Product Graphs

11:35 AM - 11:40 AM

Co-authors: Joshua Loyal (Florida State University), Joshua Loyal (Florida State University)

Gibbs posterior Dynamic network data Network latent space models statistical network analysis Bayesian inference Forecasting

Marginal Likelihood Estimation in Bayesian Item Response Theory Models

11:40 AM - 11:45 AM

Co-authors: Alex Nguyen, Alex Nguyen, Sally Paganin (The Ohio State University)

Bridge Sampling Bayes Factor Hierarchical Models Latent Variables Monte Carlo Methods Nonparametric Clustering

Missing data imputation via truncated Gaussian factor analysis with application to metabolomics data

11:45 AM - 11:50 AM

Co-authors: Kate Finucane (University College Dublin), Lorraine Brennan (University College Dublin), Kate Finucane (University College Dublin), Roberta De Vito (Brown University), Massimiliano Russo (The Ohio State University), Isobel Claire Gormley (University College Dublin)

Missing data Metabolomics Imputation Infinite factor model Mass spectrometry data

Modeling Binary Data with Time-Dependent Covariates: A Two-Stage Logistic Regression Approach

11:50 AM - 11:55 AM

Co-authors: Lori Selby (Arizona State University), Lori Selby (Arizona State University), Ruoqian Liu (Arizona State University), Jeffrey Wilson (Arizona State University)

Longitudinal Binary Data Two-stage Logistic Regression Time-Dependent Covariates Bayesian Priors Random Effects Models Hierarchical Models

Praxis-BGM: Prior-Augmented and Regularized Natural-Gradient Variational Inference with Gaussian Mixture Models for Transfer Learning

11:55 AM - 12:00 PM

Co-authors: Qiran Jia (University of Southern California), Jesse Goodrich (University of Southern California), Qiran Jia (University of Southern California), David Conti (University of Southern California)

Multi-omics Bayesian Clustering Mixture Model Variational Inference High-Dimensional Data Dimension Reduction

Quantile Slice Sampling

12:00 PM - 12:05 PM

Co-authors: Matthew Heiner (Brigham Young University), Matthew Heiner (Brigham Young University), Samuel Johnson, Joshua Christensen (Pentara Corporation), David Dahl (Brigham Young University)

Markov chain Monte Carlo Hybrid slice sampling Bayesian computation

Sampling from ranking models via a hit and run approach

12:05 PM - 12:10 PM

Co-authors: Chenyang Zhong (Department of Statistics, Columbia University), Chenyang Zhong (Department of Statistics, Columbia University)

Mallows permutation model ranking data hit and run algorithm Markov chain Monte Carlo mixing time scalable inference

SPEED 4: Bayesian Analysis and Computational Methods, Part 1

17 Presentations