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