2 papers
cs.LG2026
View Space: Learning Representation across Arbitrary Graphs
Dooho Lee, Myeong Kong, Minho Jeong +1
Generalizing pretrained models to unseen datasets without retraining is a central challenge toward foundation models. Achieving fully inductive inference on numerical data is parti…
cs.LG2026
Aggregation Buffer: Revisiting DropEdge with a New Parameter Block
Dooho Lee, Myeong Kong, Sagad Hamid +2
We revisit DropEdge, a data augmentation technique for GNNs which randomly removes edges to expose diverse graph structures during training. While being a promising approach to eff…