Student Brown Bag Seminar

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.

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