Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space.
CoRR, January, 2025
Graph Defense Diffusion Model.
CoRR, January, 2025
Dynamic self-training with less uncertainty for graph imbalance learning.
Expert Syst. Appl., 2025
Label-guided graph contrastive learning for semi-supervised node classification.
Expert Syst. Appl., 2024
Multi-strategy adaptive data augmentation for Graph Neural Networks.
Expert Syst. Appl., 2024
Molecular Data Programming: Towards Molecule Pseudo-labeling with Systematic Weak Supervision.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
INS-GNN: Improving graph imbalance learning with self-supervision.
Inf. Sci., August, 2023
Graph prototypical contrastive learning.
Inf. Sci., 2022
Negative samples selecting strategy for graph contrastive learning.
Inf. Sci., 2022
Similarity-based domain adaptation network.
Neurocomputing, 2022
AutoAUG : Automatic Data Augmentation for Graph Neural Networks.
Proceedings of the 5th International Conference on Algorithms, 2022
Exploring Self-training for Imbalanced Node Classification.
Proceedings of the Neural Information Processing - 28th International Conference, 2021