no code implementations • 30 Jul 2018 • Guillaume Favelier, Noura Faraj, Brian Summa, Julien Tierny
We show how to leverage spectral embedding to represent the ensemble members as points in a low-dimensional Euclidean space, where distances between points measure the dissimilarities between critical point layouts and where statistical tasks, such as clustering, can be easily carried out.