YoVDO

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

Offered By: International Centre for Theoretical Sciences via YouTube

Tags

Materials Science Courses Machine Learning Courses Neural Networks Courses Soft Matter Physics Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
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.

Syllabus

Glassy Dynamics and Plasticity: Building ML-Based Theories (Lecture 3) by Andrea J Liu


Taught by

International Centre for Theoretical Sciences

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera
Good Brain, Bad Brain: Basics
University of Birmingham via FutureLearn
Statistical Learning with R
Stanford University via edX
Machine Learning 1—Supervised Learning
Brown University via Udacity
Fundamentals of Neuroscience, Part 2: Neurons and Networks
Harvard University via edX