Data-driven model reconstruction for nonlinear wave dynamics
The use of machine learning to predict wave dynamics is a topic of growing interest, but commonly used deep-learning approaches suffer from a lack of interpretability of the trained models. Here, we present an interpretable machine learning framework for analyzing the nonlinear evolution dynamics of...
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| Main Authors: | Ekaterina Smolina, Lev Smirnov, Daniel Leykam, Franco Nori, Daria Smirnova |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2025-06-01
|
| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/2jh8-p5y2 |
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