  We introduce Schroedinger Eigenmaps, a new semi-supervised manifold learning
and recovery technique. This method is based on an implementation of graph
Schroedinger operators with appropriately constructed barrier potentials as
carriers of labeled information. We use our approach for the analysis of
standard bio-medical datasets and new multispectral retinal images.
