google-deepmind/graph_nets
Build Graph Nets in Tensorflow
This library helps machine learning engineers build models that reason about relationships and structures in data, like social networks, chemical compounds, or logistical routes. You input data represented as a graph (nodes, edges, and global properties), and it outputs an updated graph where these elements have learned relationships. It's for machine learning researchers and practitioners who want to develop advanced AI models using graph neural networks.
5,396 stars. No commits in the last 6 months.
Use this if you need to build machine learning models that process data with explicit relationship structures, such as optimizing routes or understanding complex system dynamics.
Not ideal if your data lacks inherent graph structures or if you are not comfortable working with TensorFlow and Sonnet for deep learning.
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5,396
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780
Language
Python
License
Apache-2.0
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Last pushed
Dec 12, 2022
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