Recently, Tang et. al. introduced an algorithm called the programmable graph architecture (PGA) algorithm for multiplying matrices in GL(n,mu), the generalized linear group of matrices modulo mu, ...

Graph Convolutional Networks (GCNs) are recently getting much attention in bioinformatics and chemoinformatics as a state-of-the-art machine learning approach with high accuracy. GCNs process ...

Applied Mathematics Vol.5 No.13(2014), ... Block Matrix Representation of a Graph Manifold Linking Matrix Using Continued Fractions. Fernando I. Becerra López, Vladimir N. Efremov, Alfonso M.

ABSTRACT: Let G be a finite and undirected simple graph on n vertices, A(G) is the adjacency matrix of G, λ1,λ2,...,λn are eigenvalues of A(G), then the energy of G is . In this paper, we determine ...

Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...