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Yangze Zhou

2 accepted papers

2022

OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs

NeurIPS 2022accept

This work provides the first theoretical study on the ability of graph Message Passing Neural Networks (gMPNNs) ---such as Graph Neural Networks (GNNs)--- to perform inductive out-of-distribution (OOD) link prediction tasks, where deployment (test) graph sizes are larger than training graphs. We fir…

2021

Size-Invariant Graph Representations for Graph Classification Extrapolations

ICML 2021oral

In general, graph representation learning methods assume that the train and test data come from the same distribution. In this work we consider an underexplored area of an otherwise rapidly developing field of graph representation learning: The task of out-of-distribution (OOD) graph classification,…