Graph diffusion in riemannian and euclidean spaces for multidimensional time-series decoding
The problem of decoding multidimensional time series with high variance and strong covariance between components is considered. Previously proposed prediction methods do not account for the spatial structure of time series. It is proposed to model this structure using graph-based methods, such as graph neural diffusion...