9 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 9 cited
Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification
Yu Wang, Charu Aggarwal, Tyler Derr
Recent years have witnessed the significant success of applying graph neural networks (GNNs) in learning effective node representations for classification. However, current GNNs ar…
cs.LG2021★ 4 cited
Tree Decomposed Graph Neural Network
Yu Wang, Tyler Derr
Graph Neural Networks (GNNs) have achieved significant success in learning better representations by performing feature propagation and transformation iteratively to leverage neigh…
cs.LG2021★ 2 cited
Explicit Pairwise Factorized Graph Neural Network for Semi-Supervised Node Classification
Yu Wang, Yuesong Shen, Daniel Cremers
Node features and structural information of a graph are both crucial for semi-supervised node classification problems. A variety of graph neural network (GNN) based approaches have…