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README.md

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@@ -7,7 +7,7 @@ Codebase for neural networks (SignNet and BasisNet) and experiments in the paper
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<img src="large_thumbnail.png" width=50%>
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### Experiments
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## Experiments
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`Alchemy` contains the experiments for graph-level regression on Alchemy.
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The intrinsic neural fields experiments use private code from the authors of the [original paper](https://arxiv.org/abs/2203.07967), so we do not yet publically release the SignNet codes for these.
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### Implementations
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## Implementations
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PyTorch Geometric SignNet for graph prediction: in `Alchemy`.
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DGL SignNet for graph prediction: in `GraphPrediction`.
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BasisNet for single graphs: in `LearningFilters`.
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The SignNet architecture is rather simple. Here is an example of pseudo-code for SignNet, as used for graph prediction tasks with a GNN base model:
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<img src="pseudo-code.png" width=50%>
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<img src="LPE_symmetries.png" width=50%>
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**Coming Soon:** More experiments and implementations of our models! This repo and our paper are still a work in progress.

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