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An implementation of the KAN architecture using learnable activation functions for knowledge distillation on the MNIST handwritten digits dataset. The project demonstrates distilling a three-layer teacher KAN model into a more compact two-layer student model, comparing the performance impacts of distillation versus non-distilled models.

Jupyter Notebook 48.73% Python 51.27%
kan knowledge-distillation kolmogorov-arnold-networks kolmogorov-arnold-representation mnist-classification

kan-distillation's Introduction

Hi ๐Ÿ‘‹, I'm Pranav Gupta

  • ๐Ÿ‘ฏ Iโ€™m looking to collaborate on Deep Learning Projects.

  • ๐Ÿ’ฌ Researching on Diffusion Models, Image-Text representations

  • ๐Ÿ“ซ How to reach me [email protected]

  • โšก Fun fact I am from the future and I won the Turing Award

Connect with me:

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pranavgupta2603

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