Jun 21, 2022 · We present--to the best of our knowledge--the first comprehensive benchmark for unsupervised outlier node detection on static attributed graphs called BOND.
Jun 28, 2024 · Graph outlier detection is an emerging but crucial machine learning task with numerous applications. Despite the proliferation of algorithms ...
Outlier detection (OD) on a graph refers to the task of identifying which nodes in the graph are outliers. This is a key machine learning (ML) problem that ...
Sep 16, 2022 · We present BOND, a comprehensive benchmark for unsupervised node outlier detection on attributed static graphs.
This work presents the first comprehensive unsupervised node outlier detection benchmark for graphs called UNOD, evaluating fourteen methods with backbone ...
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Abstract. Detecting which nodes in graphs are outliers is a relatively new machine learning task with numerous applications. Despite the proliferation of ...
2. • The first comprehensive benchmark for unsupervised outlier node detection. • Consolidated taxonomy of outlier nodes (structural and contextual). • ...
Aug 4, 2024 · Bibliographic details on Benchmarking Node Outlier Detection on Graphs.
Sep 26, 2022 · It features (1) unified and simple API (2) full documentation and examples (3) all you need to prepare is the data in PyG format. New features ...
Based on the analyses of extensive experimental results, we discuss the pros and cons of current UNOD methods, and point out multiple crucial and promising ...