Kuramoto Oscillators and Swarms on Manifolds for Geometry Informed
Machine Learning
Kuramoto Oscillators and Swarms on Manifolds for Geometry Informed
Machine Learning
We propose the idea of using Kuramoto models (including their higher-dimensional generalizations) for machine learning over non-Euclidean data sets. These models are systems of matrix ODE's describing collective motions (swarming dynamics) of abstract particles (generalized oscillators) on spheres, homogeneous spaces and Lie groups. Such models have been extensively studied from …