| 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 | 43 | 2023 |
| Approximation bounds for convolutional neural networks in operator learning NR Franco, S Fresca, A Manzoni, P Zunino Neural Networks 161, 129-141, 2023 | 25 | 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 | 25 | 2020 |
| 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 | 18 | 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 | 17* | 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 | 10 | 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 | 9 | 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 | 8 | 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 | 6 | 2023 |
| A practical existence theorem for reduced order models based on convolutional autoencoders NR Franco, S Brugiapaglia Foundations of Data Science, 2024 | 5 | 2024 |
| 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 | 4 | 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 |
| Deep learning enhanced cost-aware multi-fidelity uncertainty quantification of a computational model for radiotherapy P Vitullo, NR Franco, P Zunino Foundations of Data Science, 2024 | 1 | 2024 |
| OC-0510 Genetically-based Cox-NTCP models for late toxicity after prostate cancer RT T Rancati, G Eliana, M Massi, NR Franco, B Avuzzi, A Cicchetti, ... Radiotherapy and Oncology 182, S418-S420, 2023 | 1 | 2023 |
| 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 |
| Genetically-based Cox-NTCP models for late toxicity after prostate cancer RT B Avuzzi, T Rancati, E Gioscio, M Massi, NR Franco, A Cicchetti, ... European Urology Open Science 57, S111-S112, 2023 | | 2023 |
| GENETICALLY-BASED COX-NTCP MODELS FOR LATE TOXICITY AFTER PROSTATE CANCER RT T Rancati, E Gioscio, MC Massi, NR Franco, B Avuzzi, D Azria, ... Physica Medica 115, 102708, 2023 | | 2023 |
| Managing RT Schedules of Early-Stage Breast Cancer Patients with a Genetic-Dosimetric Validated Model for Late Fibrosis A Cicchetti, E Gioscio, MC De Santis, P Seibold, D Azria, A Dunning, ... International journal of radiation oncology, biology, physics 117 (2), e170-e171, 2023 | | 2023 |
| PO-2113 Evaluating and updating predictive models: a high-tech open platform to boost clinical translation A Huat, NR Franco, J Chang-Claude, A Cicchetti, S Gutiérrez-Enríquez, ... Radiotherapy and Oncology 182, S1897-S1899, 2023 | | 2023 |
| Machine learning for precision medicine: a combination of data-driven and physics based models NR Franco | | 2022 |
