Mean Curvature Flow, Neural Networks, and Applications

This course covers the learning outcomes and goals of approximating geometric interface evolution using the phase field method and neural networks. It teaches skills such as data processing, neural network training, and numerical experimentation. The teaching method involves a seminar-style talk with examples, applications, and a quantitative comparison. The intended audience includes professionals and researchers in image processing, data science, material sciences, and biology.