We introduce new smoothing estimators for complex signals on graphs, based on
a recently studied Determinantal Point Process (DPP). These estimators are
built from subsets of edges and nodes drawn according to this DPP, making up
trees and unicycles, i.e., connected components containing exactly one cycle.
We provide a Julia implementation of these estimators and study their
performance when applied to a ranking problem