From the 1 of 4 linked papers with an AI index.
1 citations · 1 across the 4 of their papers we have counts for
4 papers
Learning Subgroup Relations Using Siamese Graph Neural Networks
Tal Weissblat
The paper introduces a Siamese graph neural network that encodes Cayley graph representations of finite groups to predict whether one group is a subgroup of another, achieving abou…
From Finite Cayley Graphs to Growth of Infinite Groups
Tal Weissblat
Graph neural networks (GNNs) have recently been shown to learn algebraic properties of finite groups from their Cayley graphs [1,2]. In this work, we investigate whether such model…
Graph Neural Networks for Predicting Solvability of Finite Groups
Tal Weissblat
We present a Graph Neural Network (GNN) framework for the classification of finite groups according to their solvability. Using undirected Cayley graph representations, the propose…
A General Framework for Learning Algebraic Properties from Cayley Graphs using Graph Neural Networks
Tal Weissblat
In this work, we present a general Graph Neural Network (GNN) framework for learning algebraic properties of finite groups from their Cayley graph representations. The framework pr…