YoVDO

DeepParticle: Learning Invariant Measure by Deep Neural Network Minimizing Wasserstein Distance

Offered By: Inside Livermore Lab via YouTube

Tags

Deep Learning Courses Neural Networks Courses Partial Differential Equations Courses Stochastic Processes Courses Optimal Transport Courses Wasserstein Distances Courses Interacting Particle Systems Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore an innovative approach to solving high-dimensional partial differential equations in this one-hour webinar from Inside Livermore Lab. Delve into the DeepParticle method, which integrates deep learning, optimal transport, and interacting particle techniques to tackle challenges in computational physics. Learn how this mesh-free approach overcomes limitations of traditional methods, particularly for solutions with large gradients or concentrations at unknown locations. Examine a case study on Fisher-Kolmogorov-Petrovsky-Piskunov front speeds in incompressible flows, and discover how stochastic representation and the Feynman-Kac formula enable a genetic interacting particle algorithm. Understand the process of learning invariant measures parameterized by physical parameters using neural networks, and see how this methodology extends to learning stochastic particle dynamics in various contexts, including Keller-Segel chemotaxis systems. Gain insights from Dr. Z. Zhang, an expert in scientific computation, as he shares his research on uncertainty quantification, numerical methods for stochastic differential equations, and applications in quantum chemistry, wave propagation, and fluid dynamics.

Syllabus

DDPS | ‘DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein


Taught by

Inside Livermore Lab

Related Courses

Optimal Transport and PDE - Gradient Flows in the Wasserstein Metric
Simons Institute via YouTube
Crash Course on Optimal Transport
Simons Institute via YouTube
Learning From Ranks, Learning to Rank - Jean-Philippe Vert, Google Brain
Alan Turing Institute via YouTube
Optimal Transport for Machine Learning - Gabriel Peyre, Ecole Normale Superieure
Alan Turing Institute via YouTube
Regularization for Optimal Transport and Dynamic Time Warping Distances - Marco Cuturi
Alan Turing Institute via YouTube