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20192026
most citedConstructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach

49 citations · 271 across the 22 of their papers we have counts for

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math.DS2023★ 13 cited

Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning

Dimitrios G. Patsatzis, Gianluca Fabiani, Lucia Russo +1

We present a physics-informed machine-learning (PIML) approach for the approximation of slow invariant manifolds (SIMs) of singularly perturbed systems, providing functionals in an…

math.DS2022★ 49 cited

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

Evangelos Galaris, Gianluca Fabiani, Ioannis Gallos +2

We address a three-tier data-driven approach to solve the inverse problem in complex systems modelling from spatio-temporal data produced by microscopic simulators using machine le…