Learning and accurate generation of stochastic dynamics based on multi-model Generative Adversarial Networks. - Daniele Lanzoni; Olivier Pierre-Louis; Francesco Montalenti (CoRR, 2023)

Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired Neural Networks for the 3D microstructure evolution of materials. - Daniele Lanzoni; Andrea Fantasia; Roberto Bergamaschini; Olivier Pierre-Louis; Francesco Montalenti (CoRR, 2024)

Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired neural networks for the 3D microstructure evolution of materials via Cahn-Hilliard flow. - Daniele Lanzoni; Andrea Fantasia; Roberto Bergamaschini; Olivier Pierre-Louis; Francesco Montalenti (Mach. Learn. Sci. Technol., 2024)

Unified machine-learning framework for property prediction and time-evolution simulation of strained alloy microstructure. - Andrea Fantasia; Daniele Lanzoni; Niccolò Di Eugenio; Angelo Monteleone; Roberto Bergamaschini; Francesco Montalenti (CoRR, 2025)

Learning Kinetic Monte Carlo stochastic dynamics with Deep Generative Adversarial Networks. - Daniele Lanzoni; Olivier Pierre-Louis; Roberto Bergamaschini; Francesco Montalenti (CoRR, 2025)