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08/13/2023
SAILOR: Structural Augmentation Based Tail Node Representation Learning
Graph Neural Networks (GNNs) have achieved state-of-the-art performance ...
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06/03/2023
Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning
Oversmoothing is a common phenomenon in graph neural networks (GNNs), in...
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05/30/2023
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
While contrastive self-supervised learning has become the de-facto learn...
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05/23/2023
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs
Anomaly detection aims to distinguish abnormal instances that deviate si...
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05/18/2023
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs
The prevalence of large-scale graphs poses great challenges in time and ...
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11/20/2022
Spectral Adversarial Training for Robust Graph Neural Network
Recent studies demonstrate that Graph Neural Networks (GNNs) are vulnera...
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11/09/2022
Are All Edges Necessary? A Unified Framework for Graph Purification
Graph Neural Networks (GNNs) as deep learning models working on graph-st...
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08/15/2022
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
Recent years have seen a surge in research on dynamic graph representati...
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05/20/2022
MaskGAE: Masked Graph Modeling Meets Graph Autoencoders
We present masked graph autoencoder (MaskGAE), a self-supervised learnin...
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05/20/2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Deep graph learning has achieved remarkable progresses in both business ...
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05/05/2022
Spiking Graph Convolutional Networks
Graph Convolutional Networks (GCNs) achieve an impressive performance du...
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04/20/2022
GUARD: Graph Universal Adversarial Defense
Recently, graph convolutional networks (GCNs) have shown to be vulnerabl...
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02/15/2022
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift
Deep graph learning (DGL) has achieved remarkable progress in both busin...
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02/16/2021
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software
Graph Neural Networks (GNNs) have recently shown to be powerful tools fo...
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09/08/2020
Adversarial Attack on Large Scale Graph
Recent studies have shown that graph neural networks are vulnerable agai...
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03/10/2020