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Found 2 papers, 1 papers with code
Deep Learning of Partial Graph Matching via Differentiable Top-K
Graph matching (GM) aims at discovering node matching between graphs, by maximizing the node- and edge-wise affinities between the matched elements.
Ranked #1 on
Graph Matching
on Willow Object Class
(F1 score metric)
GlobalWalk: Learning Global-aware Node Embeddings via Biased Sampling
Popular node embedding methods such as DeepWalk follow the paradigm of performing random walks on the graph, and then requiring each node to be proximate to those appearing along with it.
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