Fengbo Tian

Graph Label Denoising via Neighborhood Agreement–Guided Expectation Maximization

Graph Neural Networks are susceptible to label noise, in which message-passing mechanisms serve as conduits for propagating erroneous supervision. Current mitigation techniques typically recover clean labels via heuristics that lack theoretical grounding, which often leads to ineffective denoising.