| Accelerating simulations of strained-film growth by deep learning: Finite element method accuracy over long time scales D Lanzoni, F Rovaris, L Martín-Encinar, A Fantasia, R Bergamaschini, ... APL Machine Learning 2 (3), 2024 | 2 | 2024 |
| Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in germanium A Fantasia, F Rovaris, O Abou El Kheir, A Marzegalli, D Lanzoni, ... The Journal of Chemical Physics 161 (1), 2024 | 2 | 2024 |
| Quantitative analysis of the prediction performance of a Convolutional Neural Network evaluating the surface elastic energy of a strained film L Martín Encinar, D Lanzoni, A Fantasia, F Rovaris, R Bergamaschini, ... arXiv e-prints, arXiv: 2405.03049, 2024 | 2 | 2024 |
| Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired neural networks for the 3D microstructure evolution of materials via Cahn–Hilliard flow D Lanzoni, A Fantasia, R Bergamaschini, O Pierre-Louis, F Montalenti Machine Learning: Science and Technology 5 (4), 045017, 2024 | | 2024 |
| Quantitative analysis of the prediction performance of a Convolutional Neural Network evaluating the surface elastic energy of a strained film LM Encinar, D Lanzoni, A Fantasia, F Rovaris, R Bergamaschini, ... arXiv preprint arXiv:2405.03049, 2024 | | 2024 |
| Accelerating Crystal Growth Simulations by Convolutional Neural Networks D Lanzoni, L Martín-Encinar, F Rovaris, A Fantasia, F Montalenti, ... Abstract book of IWMCG11, 2024 | | 2024 |
| Simulating morphological evolutions by Convolutional Neural Networks D Lanzoni, F Rovaris, A Fantasia, L Martı́n-Encinar, F Montalenti, ... Abstract book of A3M Workshop, 2024 | | 2024 |
| Unravelling Atomistic Mechanisms of Pressure-Induced Phase Transitions in Silicon Nanoindentation F Rovaris, A Marzegalli, D Lanzoni, A Fantasia, G Guojia, F Montalenti, ... Abstract Book, 2024 | | 2024 |
| Convolutional Recurrent Neural Networks for tackling materials dynamics at the mesoscale D Lanzoni, R Bergamaschini, A Fantasia, F Montalenti Abstract book of" Multiscale Materials Modeling-MMM11", 2024 | | 2024 |
| Simulations of strained films evolution: extending accessible timescales through Convolutional Neural Networks D Lanzoni, F Rovaris, L Martín-Encinar, A Fantasia, R Bergamaschini, ... Abstract book of ECOSS-37, 2024 | | 2024 |
