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cs.LG2025
Understanding Generalization in Node and Link Prediction
Antonis Vasileiou, Timo Stoll, Christopher Morris
Using message-passing graph neural networks (MPNNs) for node and link prediction is crucial in various scientific and industrial domains, which has led to the development of divers…
cs.LG2025
Survey on Generalization Theory for Graph Neural Networks
Antonis Vasileiou, Stefanie Jegelka, Ron Levie +1
Message-passing graph neural networks (MPNNs) have emerged as the leading approach for machine learning on graphs, attracting significant attention in recent years. While a large s…