Deep Learning Methods in Mathematical Physics
Speaker: Prof. Ovidiu Calin, Department of Mathematics & Statistics, Eastern Michigan University
Host: S Baskar
Title: Review of Feed-Forward Neural Networks
Time, day and date: 10:00:00 AM – 11:00:00 AM, Monday, February 16
Venue: Ramanujan Hall
Abstract: This lecture presents an introduction to feed-forward neural networks, emphasizing their mathematical structure and relevance to modern problems in physics. We discuss how neural networks are trained, why they are effec.ve function approximators, and how they can be used to model physical systems governed by differential equations. The lecture serves as a foundation for a lecture series on deep learning methods in mathematical and computational physics