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# !! Major Updates on July 13, 2024
* `model.train()` has been changed to `model.fit()`
* Some other small features are changed (e.g., create_dataset has been moved to kan.utils). I have updated and checked the notebooks in `./tutorials` are runnable on CPUs, so please refer to those for updated/new functionalities. Documentation hasn't been updated yet but will be updated soon.
* Some other small features are changed (e.g., create_dataset has been moved to kan.utils). I have updated and checked the notebooks in `./tutorials` are runnable on CPUs, so please refer to those tutorials for updated/new functionalities. Documentation hasn't been updated yet but will be updated soon.
For pypi users, this is the most recent version 0.2.0.
New functionalities include (documentation later):
* including multiplications in KANs. [Tutorial](https://github.com/KindXiaoming/pykan/blob/master/tutorials/Interp_1_Hello%2C%20MultKAN.ipynb)
* the speed mode. Speed up your KAN using `model = model.speed()` if you never use the symbolic functionalities. [Tutorial](https://github.com/KindXiaoming/pykan/blob/master/tutorials/Example_2_speed_up.ipynb)
* Compiling symbolic formulas into KANs. [Tutorial](https://github.com/KindXiaoming/pykan/blob/master/tutorials/Interp_3_KAN_Compiler.ipynb)
* Feature attribution and pruning inputs. [Tutorial](https://github.com/KindXiaoming/pykan/blob/master/tutorials/Interp_4_feature_attribution.ipynb)
# Kolmogorov-Arnold Networks (KANs)
This is the github repo for the paper ["KAN: Kolmogorov-Arnold Networks"](https://arxiv.org/abs/2404.19756). Find the documentation [here](https://kindxiaoming.github.io/pykan/). Here's [author's note](https://github.com/KindXiaoming/pykan?tab=readme-ov-file#authors-note) responding to current hype of KANs.