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Found 2 papers, 1 papers with code
Towards Fair Graph Anomaly Detection: Problem, New Datasets, and Evaluation
The Fair Graph Anomaly Detection (FairGAD) problem aims to accurately detect anomalous nodes in an input graph while ensuring fairness and avoiding biased predictions against individuals from sensitive subgroups such as gender or political leanings.
Chemical Structure Elucidation from Mass Spectrometry by Matching Substructures
We take a data driven approach to rank these structures by using neural networks to predict the presence of substructures given the mass spectrum, and matching these substructures to the candidate structures.
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