33 citations · 42 across the 6 of their papers we have counts for
Showing 2023 · cs.LGShow all
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cs.LG2023★ 8 cited
The expressive power of pooling in Graph Neural Networks
Filippo Maria Bianchi, Veronica Lachi
In Graph Neural Networks (GNNs), hierarchical pooling operators generate local summaries of the data by coarsening the graph structure and the vertex features. While considerable a…
cs.LG2023★ 33 cited
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities
Antonio Longa, Veronica Lachi, Gabriele Santin +5
Graph Neural Networks (GNNs) have become the leading paradigm for learning on (static) graph-structured data. However, many real-world systems are dynamic in nature, since the grap…