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Improving augmentation consistency for graph contrastive learning
Graph contrastive learning (GCL) enhances unsupervised graph representation by
generating different contrastive views, in which properties of augmented nodes are required …
generating different contrastive views, in which properties of augmented nodes are required …
Stochastic subgraph neighborhood pooling for subgraph classification
Subgraph classification is an emerging field in graph representation learning where the task
is to classify a group of nodes (ie, a subgraph) within a graph (eg, identifying rare diseases …
is to classify a group of nodes (ie, a subgraph) within a graph (eg, identifying rare diseases …
Subgraph representation learning with self-attention and free adversarial training
D Qin, X Tang, J Lu - Applied Intelligence, 2024 - Springer
Due to its capacity to capture subgraph information within graph data, subgraph
representation learning has garnered considerable attention in recent years. However …
representation learning has garnered considerable attention in recent years. However …
Subgraph autoencoder with bridge nodes
D Qin, X Tang, Y Huang, J Lu - Expert Systems with Applications, 2024 - Elsevier
Subgraph representation learning is a burgeoning field within graph representation
learning. However, current methods in this field face several issues, including the inability to …
learning. However, current methods in this field face several issues, including the inability to …
MPrompt: A Pretraining-Prompting Scheme for Enhanced Fewshot Subgraph Classification
M Xu - 2024 - dspace.mit.edu
Motivated by the significant progress in NLP prompt learning, there have been great
research interests recently in adopting the prompting mechanism for graph machine …
research interests recently in adopting the prompting mechanism for graph machine …
[CITATA][C] Subgraph classification through neighborhood pooling
SA Jacob - 2023