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arXiv · 2104.14652

Fast Multiscale Diffusion on Graphs

Sibylle Marcotte·Amélie Barbe·Rémi Gribonval·Titouan Vayer·Marc Sebban·Pierre Borgnat·Paulo Gonçalves
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Abstract

Diffusing a graph signal at multiple scales requires computing the action of the exponential of several multiples of the Laplacian matrix. We tighten a bound on the approximation error of truncated Chebyshev polynomial approximations of the exponential, hence significantly improving a priori estimates of the polynomial order for a prescribed error. We further exploit properties of these approximations to factorize the computation of the action of the diffusion operator over multiple scales, thus reducing drastically its computational cost.

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Sibylle Marcotte, Amélie Barbe, Rémi Gribonval, Titouan Vayer, Marc Sebban, Pierre Borgnat, Paulo Gonçalves. 2021-04-29. Fast Multiscale Diffusion on Graphs. https://arxiv.org/abs/2104.14652

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