graph neural networks

Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification
Recently, Graph Convolutional Network (GCN) has progressed significantly and gained increasing attention in hyperspectral image (HSI) …
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Heterogeneous Graph Attention Network for Small and Medium-Sized Enterprises Bankruptcy Prediction
Credit assessment for Small and Medium-sized Enterprises (SMEs) is of great interest to financial institutions such as commercial banks …
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A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Human knowledge provides a formal understanding of the world. Knowledge graphs that represent structural relations between entities …
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Graph Learning: A Survey
Graphs are widely used as a popular representation of the network structure of connected data. Graph data can be found in a wide …
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Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
Anomaly detection on attributed networks attracts considerable research interests due to wide applications of attributed networks in …
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Learning Graph Neural Networks with Positive and Unlabeled Nodes
Graph neural networks (GNNs) are important tools for transductive learning tasks, such as node classification in graphs, due to their …
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Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Graph-based Semi-Supervised Learning (SSL) aims to transfer the labels of a handful of labeled data to the remaining massive unlabeled …
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Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement
Recent works on One-Shot Neural Architecture Search (NAS) mostly adopt a bilevel optimization scheme to alternatively optimize the …
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Graph Geometry Interaction Learning
While numerous approaches have been developed to embed graphs into either Euclidean or hyperbolic spaces, they do not fully utilize the …
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Graph Stochastic Neural Networks for Semi-supervised Learning
Graph Neural Networks (GNNs) have achieved remarkable performance in the task of the semi-supervised node classification. However, most …
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