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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.11209 |
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| _version_ | 1866909841394499584 |
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| author | Alboré, Nicola Di Antonio, Gabriele Coccetti, Fabrizio Gabrielli, Andrea |
| author_facet | Alboré, Nicola Di Antonio, Gabriele Coccetti, Fabrizio Gabrielli, Andrea |
| contents | We propose a new reservoir computing method for forecasting high-resolution spatiotemporal datasets. By combining multi-resolution inputs from coarser to finer layers, our architecture better captures both local and global dynamics. Applied to Sea Surface Temperature data, it outperforms standard parallel reservoir models in long-term forecasting, demonstrating the effectiveness of cross-layers coupling in improving predictive accuracy. Finally, we show that the optimal network dynamics in each layer become increasingly linear, revealing the slow modes propagated to subsequent layers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_11209 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cross-Scale Reservoir Computing for large spatio-temporal forecasting and modeling Alboré, Nicola Di Antonio, Gabriele Coccetti, Fabrizio Gabrielli, Andrea Machine Learning Computational Physics We propose a new reservoir computing method for forecasting high-resolution spatiotemporal datasets. By combining multi-resolution inputs from coarser to finer layers, our architecture better captures both local and global dynamics. Applied to Sea Surface Temperature data, it outperforms standard parallel reservoir models in long-term forecasting, demonstrating the effectiveness of cross-layers coupling in improving predictive accuracy. Finally, we show that the optimal network dynamics in each layer become increasingly linear, revealing the slow modes propagated to subsequent layers. |
| title | Cross-Scale Reservoir Computing for large spatio-temporal forecasting and modeling |
| topic | Machine Learning Computational Physics |
| url | https://arxiv.org/abs/2510.11209 |