Generalization of neural network models for complex network dynamics
Abstract Differential equations are a ubiquitous tool to study dynamics, ranging from physical systems to complex systems, where a large number of agents interact through a graph. Data-driven approximations of differential equations present a promising alternative to traditional methods for uncoveri...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2024-10-01
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Series: | Communications Physics |
Online Access: | https://doi.org/10.1038/s42005-024-01837-w |