Data-driven Learning of Interaction Laws in Multispecies Particle Systems with Gaussian Processes: Convergence Theory and Applications
PositiveArtificial Intelligence
This article presents an innovative Gaussian process framework designed to learn interaction laws in multispecies particle systems using trajectory data. It builds on previous work by extending the convergence theory to more complex models, showcasing the potential for multiscale modeling where simple rules lead to intricate behaviors.
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