An adjoint-free algorithm for conditional nonlinear optimal perturbations (CNOPs) via sampling
<p>In this paper, we propose a sampling algorithm based on state-of-the-art statistical machine learning techniques to obtain conditional nonlinear optimal perturbations (CNOPs), which is different from traditional (deterministic) optimization methods.<span class="inline-formula"&...
| Published in: | Nonlinear Processes in Geophysics |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-07-01
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| Online Access: | https://npg.copernicus.org/articles/30/263/2023/npg-30-263-2023.pdf |