Transformers are Graph Neural Networks!
MIT License
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PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, Gr...
Pytorch implementation of convolutional neural network visualization techniques
Network-to-Network Translation with Conditional Invertible Neural Networks
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2...
My implementation of the original GAT paper (Veličković et al.). I've additionally included the p...
Geometric GNN Dojo provides unified implementations and experiments to explore the design space o...
CaptionBot : Sequence to Sequence Modelling where Encoder is CNN(Resnet-50) and Decoder is LSTMCe...
The author's officially unofficial PyTorch BigGAN implementation.
Transformer: PyTorch Implementation of "Attention Is All You Need"
Graph Neural Network Library for PyTorch
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relat...
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.