Chapter 7 - Deep learning of spectral geometry

Abstract

The deep learning-based geometry is a data-driven technique, and we consider it as data geometry. The chapter describes the main mathematical ideas behind geometric deep learning and provides development details for several applications in shape analysis and synthesis, especially in spectral geometry. With the detailed review of recent geometric deep learning techniques, we illustrate a clear picture of the key concepts and techniques, as well as the related applications. We also provide practical implementation details for the methods presented in these works.