Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

A Physics-Based Reduced Order Model Capturing the Topology of Dynamical Manifolds

Inside Livermore Lab via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a transformational approach to dynamics inspired by Mallat's Scattering Transformation in this 1-hour 23-minute talk by Michael E. Glinsky, CEO of BNZ Energy Inc. Delve into the Heisenberg Scattering Transformation, a method based on a canonical approach that projects dynamics onto the Renormalization Basis. Learn how this technique constrains dynamics to a low-dimensional complex linear subspace and quantifies topology using a Multi-Layer Perceptron. Discover the application of this approach in creating a fast surrogate model for 2D pulsed power liner implosions (MagLIF). Gain insights from Glinsky's 30-year career in data science, deep learning, and Bayesian data analysis, and understand how this innovative method can be applied to make better business decisions in various industries.

Syllabus

DDPS | A physics-based Reduced Order Model capturing the topology of dynamical manifolds

Taught by

Inside Livermore Lab

Reviews

Start your review of A Physics-Based Reduced Order Model Capturing the Topology of Dynamical Manifolds

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.