Hierarchical equivariant graph neural networks for forecasting collective motion in vortex clusters and microswimmers
Published in Communications Physics, 2025
Recommended citation: Linot, A. J., Hang, H., Kanso, E., and Taira, K. (2025). Hierarchical equivariant graph neural networks for forecasting collective motion in vortex clusters and microswimmers. Communications Physics, 8, 515. https://doi.org/10.1038/s42005-025-02417-2
This work develops hierarchical and equivariant graph neural networks for modeling collective dynamics with short- and long-range interactions, including point-vortex clusters and microswimmers.
Recommended citation: Linot, A. J., Hang, H., Kanso, E., and Taira, K. (2025). Hierarchical equivariant graph neural networks for forecasting collective motion in vortex clusters and microswimmers. Communications Physics, 8, 515. doi.org/10.1038/s42005-025-02417-2