Interpolating Missing Spatial Data Using Graph Laplacian Eigenbasis

This paper addresses the problem of interpolating missing spatial data at the vertices of a connected undirected simple graph. We show that, by exploiting the eigenbasis of the graph Laplacian, all missing values can be reconstructed even from a single observation. This work establishes a novel connection between spatial statistics and spectral graph theory.