geometric-gnn-dojo
Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks. (by chaitjo)
pna
Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric (by lukecavabarrett)
| geometric-gnn-dojo | pna | |
|---|---|---|
| 4 | 5 | |
| 426 | 329 | |
| - | - | |
| 3.8 | 1.8 | |
| 11 months ago | almost 2 years ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
geometric-gnn-dojo
Posts with mentions or reviews of geometric-gnn-dojo.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-01.
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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
pna
Posts with mentions or reviews of pna.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-16.
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[D] Machine Learning - WAYR (What Are You Reading) - Week 130
/u/CatalyzeX_code_bot: Paper link
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[D] Machine Learning - WAYR (What Are You Reading) - Week 129
Code for https://arxiv.org/abs/2004.05718 found: https://github.com/lukecavabarrett/pna
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[D] Machine Learning - WAYR (What Are You Reading) - Week 128
In this regard, I came across the Principal Neighborhood Aggregation paper which aggregates information from neighbors based on different aggregators (1st, 2nd, and higher-order moments like mean, std, kurtosis, etc.). Additionally, the authors also introduce a scaler based on the degree of the node. It basically amplifies or attenuates the incoming information from the neighboring nodes. The code implementation is available here. Reach out to me if you want to discuss more!
What are some alternatives?
When comparing geometric-gnn-dojo and pna you can also consider the following projects:
graphein - Protein Graph Library
gnn-lspe - Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
torchdrug - A powerful and flexible machine learning platform for drug discovery