Improving augmentation consistency for graph contrastive learning

W Bu, X Cao, Y Zheng, S Pan - Pattern Recognition, 2024 - Elsevier
Graph contrastive learning (GCL) enhances unsupervised graph representation by
generating different contrastive views, in which properties of augmented nodes are required …

Stochastic subgraph neighborhood pooling for subgraph classification

SA Jacob, P Louis, A Salehi-Abari - Proceedings of the 32nd ACM …, 2023 - dl.acm.org
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 …

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 …

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 …

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 …

[CITATA][C] Subgraph classification through neighborhood pooling

SA Jacob - 2023