Stochastic Emulation for Efficient Onshore Probabilistic Tsunami Hazard Assessment
Abstract Machine learning is emerging as a promising strategy for modeling tsunami inundation at reduced computational cost. To enable probabilistic outputs that capture emulator uncertainty, we employ an ensemble of stochastic encoder‐decoder emulators with dropout‐based stochastic forward pass. Tr...
Furkejuvvon:
| Váldodahkkit: | , , , , , , , , |
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| Materiálatiipa: | Artigo |
| Giella: | Inglês |
| Almmustuhtton: |
Wiley
2026-04-01
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| Ráidu: | Journal of Geophysical Research: Machine Learning and Computation |
| Fáttát: | |
| Liŋkkat: | https://doi.org/10.1029/2025JH001100 |
| Fáddágilkorat: |
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