218 citations · 222 across the 5 of their papers we have counts for
4 papers · 1 filter
LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation
Lin Du, Lu Bai, Jincheng Li +5
Graph Neural Networks (GNNs) have emerged as a dominant paradigm for graph classification. Specifically, most existing GNNs mainly rely on the message passing strategy between neig…
Learning Defense Transformers for Counterattacking Adversarial Examples
Jincheng Li, Jiezhang Cao, Yifan Zhang +2
Deep neural networks (DNNs) are vulnerable to adversarial examples with small perturbations. Adversarial defense thus has been an important means which improves the robustness of D…
Internal Wasserstein Distance for Adversarial Attack and Defense
Qicheng Wang, Shuhai Zhang, Jiezhang Cao +3
Deep neural networks (DNNs) are known to be vulnerable to adversarial attacks that would trigger misclassification of DNNs but may be imperceptible to human perception. Adversarial…
Fair Meta-Learning For Few-Shot Classification
Chen Zhao, Changbin Li, Jincheng Li +1
Artificial intelligence nowadays plays an increasingly prominent role in our life since decisions that were once made by humans are now delegated to automated systems. A machine le…