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