## Speaker:

Jack Xin

## Speaker Link:

## Institution:

UCI

## Time:

Friday, February 4, 2022 - 4:00pm

## Host:

## Location:

MSTB 124

We introduce mathematical methods for reducing complexity of deep neural networks

in the context of computer vision for mobile and IoT applications such as sparsification and differentiable architecture search. We also describe applications in infectious disease prediction, and a deep learning and optimal

transport (the deep particle) method in predicting invariant measures of

stochastic dynamical systems arising in partial differential

equation (PDE) modeling of transport in chaotic flows (e.g. rapid stirring of coffee and milk, raging forest fires in the wind).