Comparison of Machine Learning and gPC-based proxy solutions for an efficient Bayesian identification of fracture parameters
Šodan, M and Urbanics, András and Friedman, Noémi and Stanic, A and Nikolić, M (2025) Comparison of Machine Learning and gPC-based proxy solutions for an efficient Bayesian identification of fracture parameters. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 436. ISSN 0045-7825 10.1016/j.cma.2024.117686
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Official URL: https://doi.org/10.1016/j.cma.2024.117686
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány |
| Divisions: | Informatics Laboratory |
| SWORD Depositor: | MTMT Injector |
| Depositing User: | MTMT Injector |
| Date Deposited: | 08 Apr 2025 14:49 |
| Last Modified: | 08 Apr 2025 14:49 |
| URI: | https://eprints.sztaki.hu/id/eprint/10898 |
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