Physics-informed neural networks approach for 1D and 2D Gray-Scott systems. - Fabio Giampaolo; Mariapia De Rosa; Pian Qi; Stefano Izzo; Salvatore Cuomo (Adv. Model. Simul. Eng. Sci., 2022)

A Local Boundedness Result for a Class of Obstacle Problems with Non-Standard Growth Conditions. - Mariapia De Rosa; Antonio Giuseppe Grimaldi (J. Optim. Theory Appl., 2022)

Modelling the COVID-19 infection rate through a Physics-Informed learning approach. - Mariapia De Rosa; Fabio Giampaolo; Francesco Piccialli; Salvatore Cuomo (PDP, 2023)

A physics-informed deep learning approach for solving strongly degenerate parabolic problems. - Pasquale Ambrosio; Salvatore Cuomo; Mariapia De Rosa (CoRR, 2023)

Solving groundwater flow equation using physics-informed neural networks. - Salvatore Cuomo; Mariapia De Rosa; Fabio Giampaolo; Stefano Izzo; Vincenzo Schiano Di Cola (Comput. Math. Appl., 2023)

Railway safety through predictive vertical displacement analysis using the PINN-EKF synergy. - Salvatore Cuomo; Mariapia De Rosa; Francesco Piccialli; Laura Pompameo (Math. Comput. Simul., 2024)