Research at the Interface of Applied Mathematics and Machine Learning

Research at the Interface of Applied Mathematics and Machine Learning

Lars Ruthotto, Emory University, lecturer

December 8-12, 2025 at University of Houston

Yunhui He, yhe43@uh.edu, organizer

website: http://www.math.uh.edu/cbms-amml

Lecture Notes

Lecture Slides:

Lecture 1: Machine Learning Overview

Lecture 2: Neural Network Architectures and Loss Functions

Lecture 3: Optimization for Machine Learning

Lecture 4: Modern Theory of Stochastic Gradient Descent

Lecture 5: Efficient Optimization Methods

Lecture 6: PDE Framework for Generative Modeling

Lecture 7: Scientific Machine Learning for PDEs

Lecture 8: High-Dimensional PDEs

Lecture 9: Machine Learning for Inverse Problems

Lecture 10: Mathematical Discovery and Verification