Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach

no code implementations • 31 Jan 2022 • Evangelos Galaris, Gianluca Fabiani, Ioannis Gallos, Ioannis Kevrekidis, Constantinos Siettos

For our illustrations, we implemented the proposed method to construct the one-parameter bifurcation diagram of the 1D FitzHugh-Nagumo PDEs from data generated by $D1Q3$ Lattice Boltzmann simulations.

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Construction of embedded fMRI resting state functional connectivity networks using manifold learning

no code implementations • 25 May 2020 • Ioannis Gallos, Evangelos Galaris, Constantinos Siettos

We construct embedded functional connectivity networks (FCN) from benchmark resting-state functional magnetic resonance imaging (rsfMRI) data acquired from patients with schizophrenia and healthy controls based on linear and nonlinear manifold learning algorithms, namely, Multidimensional Scaling (MDS), Isometric Feature Mapping (ISOMAP) and Diffusion Maps.