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Artículo
Analysis of the parametric correlation in mathematical modeling of In vitro glioblastoma evolution using copulas
(MDPI, 2021)
Modeling and simulation are essential tools for better understanding complex biological processes, such as cancer evolution. However, the resulting mathematical models are often highly non-linear and include many parameters, ...
Artículo
A new reliability-based data-driven approach for noisy experimental data with physical constraints
(Elsevier, 2018-01)
Data Science has burst into simulation-based engineering sciences with an impressive impulse. However, data are never uncertainty-free and a suitable approach is needed to face data measurement errors and their intrinsic ...
Artículo
An unsupervised data completion method for physically-based data-driven models
(Elsevier, 2019-02)
Data-driven methods are an innovative model-free approach for engineering and sciences, still in process of maturation. The idea behind is the combination of data analytics techniques, to handle the huge amount of data ...