Diffusion Maps & Manifold Learning

K_ij = exp(−d²/ε). Eigenvectors of the diffusion operator reveal intrinsic geometry. PCA fails on nonlinear manifolds; diffusion maps find the true structure.

3D data (Swiss Roll / Torus)

PCA projection (fails)

Diffusion Map (succeeds)

ε (kernel): 0.3