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Mathjax support in Markdown #4683

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May 20, 2022
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Mathjax support in Markdown #4683

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5143e28
markdown
rusty1s May 20, 2022
d435b11
Update README.md
rusty1s May 20, 2022
6625a8e
update
rusty1s May 20, 2022
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changelog
rusty1s May 20, 2022
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -23,6 +23,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
- Added support for graph-level outputs in `to_hetero` ([#4582](https://github.com/pyg-team/pytorch_geometric/pull/4582))
- Added `CHANGELOG.md` ([#4581](https://github.com/pyg-team/pytorch_geometric/pull/4581))
### Changed
- Math support in Markdown ([#4683](https://github.com/pyg-team/pytorch_geometric/pull/4683))
- Allow for `setter` properties in `Data` and `HeteroData` ([#4682](https://github.com/pyg-team/pytorch_geometric/pull/4682))
- Allow for optional `edge_weight` in `GCN2Conv` ([#4670](https://github.com/pyg-team/pytorch_geometric/pull/4670))
- Fixed the interplay between `TUDataset` and `pre_transform` that modify node features ([#4669](https://github.com/pyg-team/pytorch_geometric/pull/4669))
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4 changes: 1 addition & 3 deletions README.md
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Expand Up @@ -123,9 +123,7 @@ More information about evaluating final model performance can be found in the co
In addition to the easy application of existing GNNs, PyG makes it simple to implement custom Graph Neural Networks (see [here](https://pytorch-geometric.readthedocs.io/en/latest/notes/create_gnn.html) for the accompanying tutorial).
For example, this is all it takes to implement the [edge convolutional layer](https://arxiv.org/abs/1801.07829) from Wang *et al.*:

<p align="center">
<img height="40" src="https://raw.githubusercontent.com/pyg-team/pytorch_geometric/master/docs/source/_figures/edge_conv.svg?sanitize=true" />
</p>
$$x_i^{\prime} ~ = ~ \max_{j \in \mathcal{N}(i)} ~ \textrm{MLP}_{\theta} \left( [ ~ x_i, ~ x_j - x_i ~ ] \right)$$

```python
import torch
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