Papers › Learning on Graphs with Out-of-Distribution Nodes

Learning on Graphs with Out-of-Distribution Nodes

13 Aug 2023arXiv:2308.06714archive 2025-07-28

Yu Song, Donglin Wang

Graph Neural Networks (GNNs) are state-of-the-art models for performing prediction tasks on graphs. While existing GNNs have shown great performance on various tasks related to graphs, little attention has been paid to the scenario where out-of-distribution (OOD) nodes exist in the graph during training and inference. Borrowing the concept from CV and NLP, we define OOD nodes as nodes with labels unseen from the training set. Since a lot of networks are automatically constructed by programs, real-world graphs are often noisy and may contain nodes from unknown distributions. In this work, we define the problem of graph learning with out-of-distribution nodes. Specifically, we aim to accomplish two tasks: 1) detect nodes which do not belong to the known distribution and 2) classify the remaining nodes to be one of the known classes. We demonstrate that the connection patterns in graphs are informative for outlier detection, and propose Out-of-Distribution Graph Attention Network (OODGAT), a novel GNN model which explicitly models the interaction between different kinds of nodes and separate inliers from outliers during feature propagation. Extensive experiments show that OODGAT outperforms existing outlier detection methods by a large margin, while being better or comparable in terms of in-distribution classification.

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cosine_similarity songyyyy/kdd22-oodgat/utils.py official repository ran fingerprinted no licence file found · pointer only · dece6fe999782006 · report
get_acc songyyyy/kdd22-oodgat/metrics.py official repository ran no licence file found · pointer only · a1e46b338f6ac6ad · report
get_consistent_loss_new songyyyy/kdd22-oodgat/utils.py official repository ran no licence file found · pointer only · a1f38821e8c243bc · report
get_ood_performance songyyyy/kdd22-oodgat/metrics.py official repository ran no licence file found · pointer only · fc1c75c0befeceee · report
glorot_init songyyyy/kdd22-oodgat/layer.py official repository ran fingerprinted no licence file found · pointer only · bf6f0b5a65218aa0 · report
glorot_init_2 songyyyy/kdd22-oodgat/layer.py official repository ran fingerprinted no licence file found · pointer only · 2ad5e40631c11bf3 · report
generate_masks songyyyy/kdd22-oodgat/data_process.py official repository unverified no licence file found · pointer only · 415ce879b437fe80 · report
get_f1_score songyyyy/kdd22-oodgat/metrics.py official repository unverified no licence file found · pointer only · f814504939b756db · report
normalize_feature songyyyy/kdd22-oodgat/data_process.py official repository unverified no licence file found · pointer only · f40df564d22a1703 · report

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Graph AttentionGraph LearningOutlier Detection

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