The University of Arizona: Bayesian Optimal Experimental Design Via Exact Variational Approximations

Bayesian optimal experimental design (BOED) is a framework that uses statistical models and decision making under uncertainty to optimize the cost and performance of a scientific experiment.

Mutual information (MI) is a commonly adopted utility function in BOED. While theoretically appealing, MI evaluation poses a significant computational burden for most real world applications, where the data generating distribution is intractable, but sampling from it is possible. A common approach is Variational Approximations where the intractable distribution is approximated by a more computationally friendly approximation. In this talk, we will introduce a new variational method to approximating MI and explore its use in some common examples.

Series: Program in Applied Mathematics Brown Bag Seminar

1:00 PM

Hybrid: Math 402/Online

Presenter: Caleb Dahlke, Program in Applied Mathematics, University of Arizona

Place: Math, 402 and Zoom:   https://arizona.zoom.us/j/82075792519  Password:  150721

  • Audience: Adult
  • Genre: Mathematics
  • Type: Hybrid, Presentation

The event is finished.

Date

Nov 12 2021
Expired!

Time

1:00 pm - 2:00 pm

Cost

Free

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Location

The University of Arizona Mathematics Building
617 N. Santa Rita Ave., Tucson, AZ, 85721
Website
https://www.math.arizona.edu/about/building

Location 2

Online

Organizer

The University of Arizona College of Mathematics
Phone
(520) 621-6866
Website
https://crr.math.arizona.edu/
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