| Deep learning for laboratory earthquake prediction and autoregressive forecasting of fault zone stress L Laurenti, E Tinti, F Galasso, L Franco, C Marone Earth and Planetary Science Letters 598, 117825, 2022 | 49 | 2022 |
| DiffSD: Diffusion models for seismic denoising D Trappolini, L Laurenti, E Tinti, F Galasso, C Marone, A Michelini EGU General Assembly Conference Abstracts, EGU-13811, 2023 | 1 | 2023 |
| Probing the Evolution of Fault Properties During the Seismic Cycle with Deep Learning L Laurenti, G Paoletti, E Tinti, F Galasso, C Collettini, C Marone | | 2024 |
| Cold diffusion model for seismic denoising D Trappolini, L Laurenti, G Poggiali, E Tinti, F Galasso, A Michelini, ... Journal of Geophysical Research: Machine Learning and Computation 1 (2 …, 2024 | | 2024 |
| Deep learning to predict time to failure of lab foreshocks and earthquakes from fault zone raw acoustic emissions L Laurenti, C Johnson, E Tinti, F Galasso, P Johnson, C Marone EGU24, 2024 | | 2024 |
| Further investigations in Deep Learning for earthquake physics: Analyzing the role of magnitude and location in model performance G Paoletti, L Laurenti, E Tinti, F Galasso, C Collettini, C Marone EGU24, 2024 | | 2024 |
| CDiffSD: Cold Diffusion Model for seismic denoising D Trappolini, L Laurenti, E Tinti, F Galasso, A Michelini, C Marone AGU Fall Meeting Abstracts 2023 (384), S31E-0384, 2023 | | 2023 |
| Differentiating foreshocks and aftershocks with Deep Learning to analyze fault zone properties evolution L Laurenti, G Paoletti, E Tinti, F Galasso, L Franco, C Collettini, C Marone AGU Fall Meeting Abstracts 2023 (395), S31E-0395, 2023 | | 2023 |
| Using Deep Learning to understand variations in fault zone properties: distinguishing foreshocks from aftershocks L Laurenti, G Paoletti, E Tinti, F Galasso, L Franco, C Collettini, C Marone EGU General Assembly Conference Abstracts, EGU-5810, 2023 | | 2023 |
