Bernstein polynomial estimation provides a robust nonparametric technique for approximating both density and distribution functions. Based on the properties of Bernstein polynomials, which uniformly ...

The statistical physics of graphs and partition functions represents a vibrant intersection of graph theory, statistical mechanics and computational complexity. By summing over an ensemble of ...

Abstract: This paper presents a polynomial approximation method for filtering of signals defined on directed graphs. For spectral graph filtering, the polynomial approximation is often used to avoid ...

Abstract: We investigate graph convolution networks with efficient learning from higher-order graph convolutions and direct learning from adjacency matrices for node classification. We revisit the ...

Overview This project implements algorithms from the paper "Tracking Paths in Polynomial Time", which explores solutions to the Tracking Paths Problem—determining a minimal set of vertices (or edges) ...