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Invited Paper Session

Innovative Methodologies for Spatiotemporal Modeling and Inference

Mon, Aug 4, 8:30 AM - 10:20 AM Room CC-202C Music City Center

Ning NingOrganizerNing NingChair

General Methodology co: Section on Statistical Computingco: International Association for Statistical Computing Applied

6 Presentations

100 square miles: The Integration of Information for Understanding Risk

8:35 AM - 8:50 AM

Katherine Ensor (Rice University)

Accelerated Inference for Partially Observed Markov Processes using Automatic Differentiation

8:50 AM - 9:05 AM

Edward Ionides (University of Michigan)

Bayesian Flexible Modeling of Spatially Resolved Transcriptomic Data

9:05 AM - 9:20 AM

Bani Mallick (Texas A&M University)

Co-authors: Yang Ni (Texas A&M University), Arhit Chakrabarti (Texas A&M), Valeriya Rogovchenko (Texas A&M University)

Spatial transcriptomic Data Bayesian Modeling Spatial clustering Gene Networks MCMC computation

Mixing time of the conditional backward sampling particle filter

9:20 AM - 9:35 AM

sumeetpal singh (University of Wollongong)

Conditional Particle Filter Gibbs Sampling State-space model Mixing time Unbiased estimation Smoothing

Stream-level flow matching from a Bayesian decision theoretic perspective

9:35 AM - 9:50 AM

Li Ma (Duke University)

generative models normalizing flows nonparametric methods latent variable models hierarchical models

Variational Bayesian inference of dynamical system models

9:50 AM - 10:05 AM

Samuel Kou (Harvard University)

ordinary differential equations Gaussian process manifold constraint gradient descent variational Bayes missing component

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