FedCIGAR improves federated graph anomaly detection via normal-graph reconstruction, client node gating, and server sliding-window clustering, claiming better performance than prior methods under data heterogeneity.
A deep learning approach to antibiotic discovery.Cell, 180(4):688–702
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-level Anomaly Detection
FedCIGAR improves federated graph anomaly detection via normal-graph reconstruction, client node gating, and server sliding-window clustering, claiming better performance than prior methods under data heterogeneity.