Accelerating Algebraic Multigrid Methods via Artificial Neural Networks. - Paola F. Antonietti; Matteo Caldana; Luca Dedè (CoRR, 2021)

A deep learning algorithm to accelerate algebraic multigrid methods in finite element solvers of 3D elliptic PDEs. - Matteo Caldana; Paola F. Antonietti; Luca Dede' (Comput. Math. Appl., 2024)

Neural Ordinary Differential Equations for Model Order Reduction of Stiff Systems. - Matteo Caldana; Jan S. Hesthaven (CoRR, 2024)

Discovering artificial viscosity models for discontinuous Galerkin approximation of conservation laws using physics-informed machine learning. - Matteo Caldana; Paola F. Antonietti; Luca Dede' (J. Comput. Phys., 2025)

MAGNET: an open-source library for mesh agglomeration by Graph Neural Networks. - Paola F. Antonietti; Matteo Caldana; Ilario Mazzieri; Andrea Re Fraschini (CoRR, 2025)