BriefGPT.xyz
Dec, 2021
无需数据增强的图自监督学习
Augmentation-Free Self-Supervised Learning on Graphs
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Namkyeong Lee, Junseok Lee, Chanyoung Park
TL;DR
本文提出了一种新的基于图形的自监督学习框架AFGRL,能够为节点分类、聚类和相似性搜索等节点级任务提供更好的性能,而这种方法不需要设计复杂的数据增强技巧。
Abstract
Inspired by the recent success of self-supervised methods applied on images,
self-supervised learning
on
graph structured data
has seen rapid growth especially centered on augmentation-based contrastive methods.
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