Message Passing Neural Networks for Atomistic Systems - Molecules
Institute for Pure & Applied Mathematics (IPAM) via YouTube
Learn EDR Internals: Research & Development From The Masters
PowerBI Data Analyst - Create visualizations and dashboards from scratch
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Explore message passing neural networks for atomistic systems in molecules through this 24-minute conference talk presented by Mihail Bogojeski from Technische Universität Berlin. Recorded on April 1, 2022, at IPAM's Multiscale Approaches in Quantum Mechanics Workshop, the presentation delves into the application of advanced machine learning techniques in quantum mechanics. Gain insights into how these neural networks can be utilized to model and analyze molecular structures at the atomic level. Discover the potential implications of this approach for various fields, including materials science, computational chemistry, and drug discovery.
Syllabus
Mihail Bogojeski - Message passing neural networks for atomistic systems: Molecules - IPAM at UCLA
Taught by
Institute for Pure & Applied Mathematics (IPAM)