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cs.LG2022★ 12 cited
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks
Davide Buffelli, Pietro Liò, Fabio Vandin
In the past few years, graph neural networks (GNNs) have become the de facto model of choice for graph classification. While, from the theoretical viewpoint, most GNNs can operate…
cs.LG2022
Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach
Davide Buffelli, Fabio Vandin
Graph Neural Networks (GNNs) have become the state-of-the-art method for many applications on graph structured data. GNNs are a model for graph representation learning, which aims…