40 citations · 98 across the 9 of their papers we have counts for
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cs.LG2022★ 3 cited
Scalable Spatiotemporal Graph Neural Networks
Andrea Cini, Ivan Marisca, Filippo Maria Bianchi +1
Neural forecasting of spatiotemporal time series drives both research and industrial innovation in several relevant application domains. Graph neural networks (GNNs) are often the…
cs.LG2022★ 19 cited
Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations
Ivan Marisca, Andrea Cini, Cesare Alippi
Modeling multivariate time series as temporal signals over a (possibly dynamic) graph is an effective representational framework that allows for developing models for time series a…