Saeid Sadeghnejad

Partial differential equations in the age of machine learning: a critical synthesis of classical, machine learning, and hybrid methods

Abstract Partial differential equations (PDEs) govern physical phenomena across the full range of scientific scales, yet their computational solution remains one of the defining challenges of modern science. This critical review examines two mature but epistemologically distinct...

Modeling of Cu, Pb, and Zn reservoirs in crustal igneous rocks using explainable machine learning

Abstract Here we use explainable machine-learning (ML) analysis to determine which variables, so-called features, are most important for the prediction of trace concentrations of Cu, Pb, and Zn in a large data set for igneous rocks. After data filtering and preparation, a gradien...