What is the role of Laplacian eigenmaps in dimensionality reduction?

Laplacian eigenmaps embed data using eigenvectors of the graph Laplacian.

Laplacian eigenmaps construct a nearest-neighbor graph and compute the graph Laplacian. The embedding is obtained using eigenvectors corresponding to the smallest non-zero eigenvalues, preserving local neighborhood structure and manifold geometry.