4 papers
Spectrum Estimation through Kirchhoff Random Forests
Simon Barthelmé, Fabienne Castell, Alexandre Gaudillière +3
Given a non-oriented edge-weighted graph, we show how to make some estimation of the associated Laplacian eigenvalues through Monte Carlo evaluation of spectral quantities computed…
Biology-driven assessment of deep learning super-resolution imaging of the porosity network in dentin
Lauren Anderson, Lucas Chatelain, Nicolas Tremblay +3
The mechanosensory system of teeth is currently believed to partly rely on Odontoblast cells stimulation by fluid flow through a porosity network extending through dentin. Visualiz…
Estimating a graph's spectrum via random Kirchhoff forests
Simon Barthelmé, Fabienne Castell, Alexandre Gaudillière +3
Exact eigendecomposition of large matrices is very expensive, and it is practically impossible to compute exact eigenvalues. Instead, one may set a more modest goal of approaching…
Random Multi-Type Spanning Forests for Synchronization on Sparse Graphs
Hugo Jaquard, Pierre-Olivier Amblard, Simon Barthelmé +1
Random diffusions are a popular tool in Monte-Carlo estimations, with well established algorithms such as Walk-on-Spheres (WoS) going back several decades. In this work, we introdu…