KANLab: TensorFlow Playground for Kolmogorov-Arnold Networks

Lukas Niehaus, Robin Rawiel, Ulf Krumnack

KANLab: TensorFlow Playground for Kolmogorov-Arnold Networks: 6 upvotes on Hugging Face Daily Papers, #35 of 44 papers on 2026-10-26. Day-by-day upvote history.

KANLab is a browser-based visualization tool designed to interactively teach the core concepts of Kolmogorov-Arnold Networks (KAN), forked from the widely successful TensorFlow Playground. To maximize educational clarity, KANLab omits residual connections and learnable scaling parameters found in modern KAN implementations, ensuring that displayed B-spline activation curves directly correspond to their underlying trainable control points. Users can inspect and modify activation functions, initialization schemes and observe gradient descent correcting manual disruptions. Furthermore, user can explore phenomena such as activation variance, interactive pruning, and re\-/training within a compact 2D machine learning setting. KANLab is open-source and available at https://kanlab.app/

Paper page on Hugging Face · arXiv

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