Representation Stability

The python code of Graph Neural Network (GRN). Recent studies have shown that the predictive performance of graph neural networks (GNNs) is inconsistent and varies across different experimental runs, even with identical parameters. The prediction variability limits GNNs' applicability, and the underlying reasons remain unclear. We have identified a key factor contributing to this issue: the oscillation of some nodes' predicted classes during GNN training.