Update README.md

Co-authored-by: Matthias Fey <[email protected]>
pyg-team · Oct 5, 2023 · 9f22508 · 9f22508
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@@ -51,8 +51,6 @@ Models in PyTorch Frame follow a modular design of `FeatureEncoder`, `TableConv`
 
 We list currently supported deep tabular models:
 
-**Models:**
-
 * **[Trompt](https://pytorch-geometric.readthedocs.io/en/latest/generated/torch_frame.nn.models.SchNet.html)** from Chen *et al.*: [Trompt: Towards a Better Deep Neural Network for Tabular Data](https://arxiv.org/abs/2305.18446) (ICML 2023) [[**Example**](https://github.com/pyg-team/pytorch-frame/blob/master/examples/trompt.py)]
 * **[FT Transformer](https://pytorch-geometric.readthedocs.io/en/latest/generated/torch_frame.nn.models.SchNet.html)** from Gorishniy *et al.*: [Revisiting Deep Learning Models for Tabular Data](https://arxiv.org/abs/2106.11959) (NeurIPS 2021) [[**Example**](https://github.com/pyg-team/pytorch-frame/blob/master/examples/revisiting.py)]
 * **[ResNet](https://pytorch-geometric.readthedocs.io/en/latest/generated/torch_frame.nn.models.SchNet.html)** from Gorishniy *et al.*: [Revisiting Deep Learning Models for Tabular Data](https://arxiv.org/abs/2106.11959) (NeurIPS 2021) [[**Example**](https://github.com/pyg-team/pytorch-frame/blob/master/examples/revisiting.py)]