Task-oriented machine learning surrogates for tipping points of agent-based models
Abstract We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for the construction of different types of effective reduced order models from detailed agent-based simulators and the systematic multiscale numeri...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-48024-7 |