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Activity Number: 534 - Bayesian Inference with Complex Biomedical Systems
Type: Invited
Date/Time: Thursday, August 6, 2020 : 1:00 PM to 2:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #309558
Title: Probabilistic Modeling in Functional Data Analysis: Ideas and Applications
Author(s): Donatello Telesca*
Companies: University of Califonia, Los Angeles
Keywords: Bayesian Analysis; Covariance Processes; Functional Data Analysis

Motivated by applications in biomedicine, we review several ideas associated with modeling functional data. From a Bayesian perspective, flexible probability models are formulated and related to classical contributions in the theory of Gaussian processes and rank-regularized estimation. This basic construction is extended to represent highly-structured observations in functional brain imaging. Specifically, we discuss applications to electroencephalography (EEG) data, collected in connection with studies of neurocognitive development in children with Autism Spectrum Disorder (ASD).

Authors who are presenting talks have a * after their name.

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