439 citations · 2k across the 50 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.LG2024
Interpreting Temporal Graph Neural Networks with Koopman Theory
Michele Guerra, Simone Scardapane, Filippo Maria Bianchi
Spatiotemporal graph neural networks (STGNNs) have shown promising results in many domains, from forecasting to epidemiology. However, understanding the dynamics learned by these m…
cs.LG2024★ 2 cited
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi
Given a set of synchronous time series, each associated with a sensor-point in space and characterized by inter-series relationships, the problem of spatiotemporal forecasting cons…