Manifold Learning, Diffusion-Maps and Applications.

Summary: We introduce the nonlinear dimensionality reduction problem known as Manifold Learning and present the diffusion maps algorithm (Coiffman and Lafon, 2006). Dif-
fusion maps utilize the connectivity between data points through a diffusion process on the dataset. Additionally, we show some applications of this technique to 2D
tomography reconstruction when the angles are unknown

Posted on Nov 4, 2024 in Seminars, SIPo (Seminario de Investigadores Postdoctorales)