IEEE

Rotation- and Permutation-Equivariant Quantum Graph Neural Network for 3D Graph Data

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
IEEE

Permutation-Equivariant and Proximity-Aware Graph Neural Networks With Stochastic Message ...

Abstract: Graph neural networks (GNNs) are emerging machine learning models on graphs. Permutation-equivariance and proximity-awareness are two important properties highly desirable for GNNs. Both ...