wehos/awesome-graph-transformer
Papers about graph transformers.
This is a curated list of research papers on Graph Transformers, categorized by the techniques they employ for structural encoding, scalability, and various real-world applications. It compiles academic findings, allowing researchers to quickly find relevant literature on how Transformer models can be adapted to analyze graph-structured data. Researchers and academics in machine learning or artificial intelligence, particularly those focusing on graph neural networks and deep learning for structured data, would find this project useful.
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Use this if you are an AI researcher or academic looking to explore, understand, or keep up-to-date with the latest advancements and research papers on Graph Transformers.
Not ideal if you are looking for an off-the-shelf software tool, a code library, or a tutorial on how to implement Graph Transformers.
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Mar 19, 2025
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