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Found 4 papers, 2 papers with code
Technical report: Graph Neural Networks go Grammatical
This paper introduces a framework for formally establishing a connection between a portion of an algebraic language and a Graph Neural Network (GNN).
Deep graph matching meets mixed-integer linear programming: Relax at your own risk ?
Graph matching is an important problem that has received widespread attention, especially in the field of computer vision.
A Convolutional Neural Network into graph space
Convolution and pooling operators are defined in graph domain.
Graph edit distance : a new binary linear programming formulation
Moreover, a relaxation of the domain constraints in the formulations provides efficient lower bound approximations of the GED.
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