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pna
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pytorch_geometric
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geometric-gnn-dojo reviews and mentions
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Gentle Introduction to Geometric Graph Neural Networks
Geometric GNNs are an emerging class of GNNs for spatially embedded graphs in scientific and engineering applications, s.a. biomolecular structure, material science, and physical simulations. Notable examples include SchNet, DimeNet, Tensor Field Networks, and E(n) Equivariant GNNs.
https://github.com/chaitjo/geometric-gnn-dojo/blob/main/geom...
This notebook and repository aims to serve as a 'Geometric GNNs 101' introduction for newcomers.
We walk through the basics of GNNs, Geometric Deep Learning, and the PyTorch Geometric library for implementing these concepts.
Our goal is to help students understand how theory/equations connect to real code.
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[R] On the Expressive Power of Geometric Graph Neural Networks
Found relevant code at https://github.com/chaitjo/geometric-gnn-dojo + all code implementations here
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chaitjo/geometric-gnn-dojo is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of geometric-gnn-dojo is Jupyter Notebook.
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