Sfoglia per Correlatore FRANCO, NICOLA RARES
Mostrati risultati da 1 a 6 di 6
Bayesian functional neural operator: uncertainty quantification of parametric PDEs
2024/2025 CAPRARI, MARCO
Deep Learning-based reduced order models for PDEs : multi-fidelity strategies for transfer learning
2020/2021 FRAULIN, DANIEL
Graph Neural Networks based AutoEncoder in Reduced Order Modeling of Dynamical Systems
2023/2024 DEVECCHI, PIETRO
Graph Neural Networks: a Deep Learning approach for microcirculatory blood flow simulation
2023/2024 BOTTA, PAOLO
Integrating geometric, functional and topological approaches for clustering aortic morphology in Marfan patients
2023/2024 MEANTI, LUCA
Multi-outcome feature selection via anomaly detection autoencoders: an application to radiogenomics in breast cancer patients
2021/2022 Mapelli, Alessia
| Fulltext | Data | Tipo | Titolo | Autore (i) |
|---|---|---|---|---|
| 2025-07-22 | Tesi di laurea Magistrale | Bayesian functional neural operator: uncertainty quantification of parametric PDEs | CAPRARI, MARCO | |
| 2022-04-28 | Tesi di laurea Magistrale | Deep Learning-based reduced order models for PDEs : multi-fidelity strategies for transfer learning | FRAULIN, DANIEL | |
| 2024-10-10 | Tesi di laurea Magistrale | Graph Neural Networks based AutoEncoder in Reduced Order Modeling of Dynamical Systems | DEVECCHI, PIETRO | |
| 2024-07-16 | Tesi di laurea Magistrale | Graph Neural Networks: a Deep Learning approach for microcirculatory blood flow simulation | BOTTA, PAOLO | |
| 2025-04-03 | Tesi di laurea Magistrale | Integrating geometric, functional and topological approaches for clustering aortic morphology in Marfan patients | MEANTI, LUCA | |
| 2022-12-20 | Tesi di laurea Magistrale | Multi-outcome feature selection via anomaly detection autoencoders: an application to radiogenomics in breast cancer patients | Mapelli, Alessia |
Mostrati risultati da 1 a 6 di 6
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