A deep learning approach to reduced order modelling of parameter dependent partial differential equations N Franco, A Manzoni, P Zunino Mathematics of Computation 92 (340), 483-524, 2023 | 39 | 2023 |
A deep learning approach validates genetic risk factors for late toxicity after prostate cancer radiotherapy in a REQUITE multi-national cohort MC Massi, F Gasperoni, F Ieva, AM Paganoni, P Zunino, A Manzoni, ... Frontiers in oncology 10, 541281, 2020 | 22 | 2020 |
Approximation bounds for convolutional neural networks in operator learning NR Franco, S Fresca, A Manzoni, P Zunino Neural Networks 161, 129-141, 2023 | 18 | 2023 |
Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity NR Franco, MC Massi, F Ieva, A Manzoni, AM Paganoni, P Zunino, ... Radiotherapy and Oncology 159, 241-248, 2021 | 16 | 2021 |
Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces NR Franco, A Manzoni, P Zunino Journal of Scientific Computing 97 (35), 2023 | 12* | 2023 |
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition S Brivio, S Fresca, NR Franco, A Manzoni Advances in Computational Mathematics 50 (3), 33, 2024 | 6 | 2024 |
Nonlinear model order reduction for problems with microstructure using mesh informed neural networks P Vitullo, A Colombo, NR Franco, A Manzoni, P Zunino Finite Elements in Analysis and Design 229, 104068, 2024 | 5 | 2024 |
Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks NR Franco, S Fresca, F Tombari, A Manzoni Chaos: An Interdisciplinary Journal of Nonlinear Science 33 (12), 2023 | 3 | 2023 |
Learning high-order interactions for polygenic risk prediction MC Massi, NR Franco, A Manzoni, AM Paganoni, HA Park, M Hoffmeister, ... Plos one 18 (2), e0281618, 2023 | 3 | 2023 |
Deep learning based reduced order modeling of Darcy flow systems with local mass conservation WM Boon, NR Franco, A Fumagalli, P Zunino arXiv preprint arXiv:2311.14554, 2023 | 2 | 2023 |
On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields NR Franco, D Fraulin, A Manzoni, P Zunino arXiv preprint arXiv:2310.12095, 2023 | 2 | 2023 |
Deep learning enhanced cost-aware multi-fidelity uncertainty quantification of a computational model for radiotherapy P Vitullo, NR Franco, P Zunino arXiv preprint arXiv:2402.08494, 2024 | 1 | 2024 |
A practical existence theorem for reduced order models based on convolutional autoencoders NR Franco, S Brugiapaglia arXiv preprint arXiv:2402.00435, 2024 | 1 | 2024 |
Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction NR Franco, A Manzoni, P Zunino, JS Hesthaven arXiv preprint arXiv:2404.18841, 2024 | | 2024 |
Machine learning for precision medicine: a combination of data-driven and physics based models NR Franco | | 2022 |