Contributed Papers

Recent Advances in Sampling Techniques

Tue, Aug 5, 2:00 PM - 3:50 PM Room CC-102B Music City Center

Yucong LiuChair

Section on Bayesian Statistical Science

6 Presentations

Computationally Efficient Laplace Approximations for Neural Networks

2:05 PM - 2:20 PM

Co-authors: Swarnali Raha (University of Florida), Swarnali Raha (University of Florida), Kshitij Khare (University of Florida), Rohit K Patra (Linkedin Inc)

Laplace Approximation Uncertainty Quantification Posterior predictive distribution Hessian matrix Subset selection

Directed Cyclic Graph learning using covariate via MCMC

2:20 PM - 2:35 PM

Co-authors: Trisha Dawn (Texas A&M University), Yang Ni (Texas A&M University), Trisha Dawn (Texas A&M University)

Directed cyclic graphs Covariate dependent partition model Parallel Tempering MCMC Covariate dependent graphs

Hierarchical Skinny Gibbs Sampler in Logistic Regression Using Pólya-Gamma Latent Variables

2:35 PM - 2:50 PM

Co-authors: Eric Odoom (University of Cincinnati), Xuan Cao (University of Cincinnati), XIA WANG (University of Cincinnati), Jiarong Ouyang (University of Cincinnati), Eric Odoom (University of Cincinnati)

Logistic regression Pólya-Gamma distribution Hierarchical Skinny Gibbs Spike-and-Slab prior

Multifidelity Sampling for High-Dimensional Spatial Uncertainty Modeling: Application to storm surge

2:50 PM - 3:05 PM

Co-authors: Hancheng Li (University of Cincinnati), Emily Kang (University of Cincinnati), Hancheng Li (University of Cincinnati), Bledar Konomi (University of Cincinnati)

Bayesian inference EM algorithm Transport Maps

Sampling from the Random Linear Model via Stochastic Localization Up to the AMP Threshold

3:05 PM - 3:20 PM

Co-authors: Zhiyuan Yu, Han Cui (University of Illinois Urbana-Champaign), Zhiyuan Yu, Jingbo Liu (UIUC)

Approximate Message Passage(AMP)Bayesian posterior sampling Random linear models Diffusion models Stochastic localization

The Riemann Sampler: A fast, accurate, and efficient alternative to MCMC

3:20 PM - 3:35 PM

Co-authors: Michael Anderson (University of Oklahoma), Justin Dvorak, Michael Anderson (University of Oklahoma)

MCMC Algorithm Bayesian Methods Sampling Algorithm Prior Distribution and Likelihood Posterior Distribution Kernel Density Estimation