LirongWu/awesome-graph-self-supervised-learning
Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"
This is a curated collection of resources on self-supervised learning methods tailored for graph-structured data. It provides links to research papers and their associated codebases, categorized by different self-supervision strategies like contrastive, generative, and predictive learning. Data scientists, machine learning researchers, and practitioners working with complex networked data like social networks, biological networks, or knowledge graphs would find this useful for discovering new techniques.
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Use this if you are a researcher or practitioner exploring advanced, unsupervised methods to extract meaningful patterns and representations from graph datasets.
Not ideal if you are looking for a plug-and-play software tool or library for direct application, as this is a collection of academic resources.
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Aug 15, 2024
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