Sviatoslav K. Panchenko

Graph diffusion in riemannian and euclidean spaces for multidimensional time-series decoding

A model for multidimensional time-series prediction based on the combination of graph neural diffusion and Riemannian geometry of covariance representations is proposed, which simultaneously captures local temporal dynamics and global inter-component dependencies.