Graph Neural Networks for Predicting Solvability of Finite Groups

In three linesResearchers propose a GNN framework to classify finite groups by solvability using graph representations including Cayley graphs. The model learns to distinguish solvable from non-solvable groups using structural graph information alone, evaluated on groups outside the training set.

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