Mean Curvature Flow, Neural Networks, and Applications

Explore mean curvature flow, neural networks, and their applications in this comprehensive SIAM-IS Virtual Seminar talk. Delve into the challenges of approximating geometric interface evolution in various fields, including image processing, data science, material sciences, and biology. Learn how the phase field method can efficiently approximate oriented surface evolution and discover a novel approach using neural networks for non-oriented surfaces. Examine applications of this new technique in solving Steiner and Plateau problems. Gain insights into diffusion neurons, quantitative comparisons, and multifaceted character flow through numerical experiments and simulations.

Introduction
Examples
Application
Data Database
Diffusion Neuron
Motivation
Quantitative Comparison
Multifacement Character Flow
Numerical Experiment
Simulation
Conclusion
Questions