SXKDZ/awesome-self-supervised-learning-for-graphs
A curated list for awesome self-supervised learning for graphs.
This is a curated collection of resources, primarily research papers, focused on self-supervised learning techniques applied to graph-structured data. It helps researchers and machine learning practitioners explore various methods for automatically learning features from graphs without needing extensive labeled examples. The list is organized by different approaches (generative/predictive, contrastive) and includes links to papers and code.
390 stars. No commits in the last 6 months.
Use this if you are a researcher or advanced practitioner looking to understand, implement, or explore the latest self-supervised learning methods for extracting insights from graph data.
Not ideal if you are looking for an off-the-shelf software tool or a basic introduction to graph neural networks; this resource is for those already familiar with the field.
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Oct 25, 2022
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