10 citations · 18 across the 6 of their papers we have counts for
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cs.LG2021★ 10 cited
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova +3
While Graph Neural Networks (GNNs) have recently become the de facto standard for modeling relational data, they impose a strong assumption on the availability of the node or edge…
cs.LG2021★ 2 cited
GRAND: Graph Neural Diffusion
Benjamin Paul Chamberlain, James Rowbottom, Maria Gorinova +3
We present Graph Neural Diffusion (GRAND) that approaches deep learning on graphs as a continuous diffusion process and treats Graph Neural Networks (GNNs) as discretisations of an…