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Found 4 papers, 3 papers with code
Spectral Adversarial Training for Robust Graph Neural Network
In this work, we seek to address these challenges and propose Spectral Adversarial Training (SAT), a simple yet effective adversarial training approach for GNNs.
Spiking Graph Convolutional Networks
Graph Convolutional Networks (GCNs) achieve an impressive performance due to the remarkable representation ability in learning the graph information.
Modelling High-Order Social Relations for Item Recommendation
The prevalence of online social network makes it compulsory to study how social relations affect user choice.
A Survey of Adversarial Learning on Graphs
To bridge this gap, we investigate and summarize the existing works on graph adversarial learning tasks systemically.
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