Random Add-Drop Edge (RADE) jointly drops and adds edges stochastically during GNN training, with provable train-inference alignment and an adaptive rate balancer, to regularize against overfitting and mitigate over-squashing.
arXiv preprint arXiv:2201.12674 , year=
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RADE: Random Add-Drop Edge as a Regularizer
Random Add-Drop Edge (RADE) jointly drops and adds edges stochastically during GNN training, with provable train-inference alignment and an adaptive rate balancer, to regularize against overfitting and mitigate over-squashing.