Convolutional-KANs
This project extends the idea of the innovative architecture of Kolmogorov-Arnold Networks (KAN) to the Convolutional Layers, changing the classic linear transformation of the convolution to learnable non linear activations in each pixel.
Experiment with advanced image processing techniques by applying non-linear transformations to convolution layers in your projects.
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Free · no card · unsubscribe anytimeThis project extends the idea of the innovative architecture of Kolmogorov-Arnold Networks (KAN) to the Convolutional Layers, changing the classic linear transformation of the convolution to learnable non linear activations in each pixel.
Convolutional-KANs has 921 stars on GitHub. It has been forked 95 times. Convolutional-KANs is written mainly in Jupyter Notebook. It has been in active development since 2024. Convolutional-KANs is available under the MIT license. Its main topics are cnn, computer-vision, deep-learning.
What is Convolutional-KANs?
This project extends the idea of the innovative architecture of Kolmogorov-Arnold Networks (KAN) to the Convolutional Layers, changing the classic linear transformation of the convolution to learnable non linear activations in each pixel.
Is Convolutional-KANs open source?
Convolutional-KANs is an open-source project. It is released under the MIT license.
Is Convolutional-KANs free?
Yes. Convolutional-KANs is free and open source — you can use, modify and self-host it.
What license does Convolutional-KANs use?
Convolutional-KANs is available under the MIT license.
What language is Convolutional-KANs written in?
Convolutional-KANs is written mainly in Jupyter Notebook.
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