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Improve the accuracy on ogbn-papers100M with GAT model, add undirected graph on ogbn-products #9467

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Improve the accuracy to 63% for papers100M with graphSage model
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1. Improve the accuracy to 57% on ogbn-papers100M with GAT model
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Consolidate ogbn_papers_100m_gat, ogbn_products_gat.py and ogbn_produ…
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1 change: 1 addition & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

### Added

- Consolidate ogbn-products and papers100m basic examples into a single ogbn_train.py with additional improvements ([#9467](https://github.com/pyg-team/pytorch_geometric/pull/9467))
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- Added the `PatchTransformerAggregation` layer ([#9487](https://github.com/pyg-team/pytorch_geometric/pull/9487))
- Added the `nn.nlp.LLM` model ([#9462](https://github.com/pyg-team/pytorch_geometric/pull/9462))
- Added an example of training GNNs for a graph-level regression task ([#9070](https://github.com/pyg-team/pytorch_geometric/pull/9070))
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126 changes: 0 additions & 126 deletions examples/ogbn_papers_100m.py

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185 changes: 0 additions & 185 deletions examples/ogbn_products_gat.py

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