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NNTikZ

A collection of TikZ diagrams for neural network and deep learning concepts. NNTikZ is designed to provide clean and consistent figures suitable for academic papers, lecture notes, theses, and presentations. All diagrams are open source, easy to customize, and written entirely in TikZ/LaTeX. Feel free to open an issue to suggest a diagram or submit a pull request with any contributions.

Some example diagrams are shown below:

Diagram Preview
Transformer Transformer
Multi-Head Attention Multi-Head Attention
Neural Network Neural Network
Attention Mechanism Attention Mechanism
Gated Recurrent Unit (GRU) Gated Recurrent Unit
RNN Encoder–Decoder (Sutskever et al.) RNN Encoder-Decoder
Backpropagation Through Time (BPTT) Backpropagation Through Time

Citation

If you use NNTikZ in your research or project, cite simply as:

@misc{nntikz,
    author = {Fraser Love},
    title = {NNTikZ: TikZ Diagrams for Deep Learning and Neural Networks},
    year = {2024},
    publisher = {GitHub}
    url = {https://github.com/fraserlove/nntikz}
}

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A collection of TikZ diagrams of neural networks and deep learning concepts for academic use.

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