graphdeeplearning/graphtransformer
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
This project offers a sophisticated deep learning architecture designed for analyzing data represented as graphs. It takes in structured graph data, such as molecular structures, social networks, or knowledge graphs, and processes it to extract meaningful patterns and make predictions. This is for researchers or practitioners working on tasks like predicting molecular properties or understanding complex network relationships, who need advanced methods beyond standard neural networks.
1,019 stars. No commits in the last 6 months.
Use this if you are working with complex graph-structured data and need a powerful, attention-based deep learning model to make predictions or classify nodes/edges.
Not ideal if your data is primarily sequential text or images, or if you prefer simpler machine learning models for graph analysis.
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1,019
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150
Language
Python
License
MIT
Category
Last pushed
Jul 27, 2021
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