most citedGraph Neural Networks for Predicting Solvability of Finite Groups

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2026★ 1 cited

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…

cs.LG2026

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…

math.GR2026

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…

math.CA2021

A characterization of spaces of homogeneous type induced by continuous ellipsoid covers of

Marcin Bownik, Baode Li, Tal Weissblat

We study the relationship between the concept of a continuous ellipsoid cover of , which was introduced by Dahmen, Dekel, and Petrushev, and the space of homogene…