kaize0409 / DND-NET

Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise, KDD 2024

DnD-NeT offers a new solution to tackle the two problems from both the model architecture and algorithm perspectives, reviving the utility of message passing and pseudo labels in the problem of semi-supervised node classification with noisy labels. Specifically, DnD-NeT involves a label-noise robust GNN equipped with a reliable graph pseudo labeling algorithm, which can attain both effectiveness and efficiency when solving the studied problem. Extensive experiments demonstrate its state-of-the-art performance in semi-supervised node classification with varying levels of label noise.

Embedding space visulization on Cora-ML (left) and CiteSeer (right)

To run the code:

python main.py

Run on ogbn-arxiv:

python main_arix.py