Awesome Network Embedding
A curated list of network embedding techniques, including papers, implementations, and related resources for graph representation learning.
What is Awesome Network Embedding?
Awesome Network Embedding is a curated GitHub repository that aggregates academic papers, code implementations, and resources related to network embedding techniques. It addresses the problem of navigating the rapidly growing literature on graph representation learning by providing a structured, community-maintained index. The list covers methods like DeepWalk, node2vec, GCNs, and knowledge graph embeddings, linking directly to research and implementations.
Researchers, graduate students, and machine learning engineers working on graph data who need a reference for state-of-the-art embedding algorithms and their codebases. It's particularly useful for those entering the field or looking to benchmark or implement graph representation learning methods.
Developers and researchers choose this list because it saves time by centralizing scattered resources, is frequently updated with new publications, and includes direct links to implementations. Its community-driven nature ensures it stays relevant and comprehensive compared to static surveys or personal collections.
Overview
A curated list of network embedding techniques.
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