Glassy Dynamics and Plasticity - Building ML-Based Theories - Lecture 3

Explore the third lecture in a series on how materials can learn by themselves, focusing on glassy dynamics and plasticity through machine learning-based theories. Delve into Andrea J Liu's innovative research on bottom-up learning in physical systems, contrasting it with the top-down approach of artificial neural networks. Gain insights into solving inverse design problems in soft matter and the development of mechanical and flow networks inspired by biological functions. Discover how this groundbreaking work is shaping our understanding of self-learning materials and their potential applications in various fields.