Efficient Kolmogorov - Arnold Network for nVidia Modulus & nVidia Modulus Sym

This repository contains an efficient implementation of Kolmogorov-Arnold Network (KAN). The original implementation of KAN is available here.

The KANLinear is based on the Efficient KAN by Blealtan Cao @Blealtan , "An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).".

It was needed a small change in the KANLinear to handle the batched tensor in modulus.

Addition of Juve 7th, 2024: added Chebyshev and Jacobu KAN for nVidia Modulus, based on #SynodicMonth and @SpaceLearner GituHub repository [1, 2], adapted to work with Modulus.

Code

The code is contained in a single python file, kan.py, in the src folder.

Addition of June 7th, 2024: two new files, chebyshev_kan.py and jacobi_kan.py offering cKANArch and jKANArch modulus model class. in examples there are avilable also the modulus code for using (and testing) the two classes.

Addition of October, 21th, 2024: three new files, rbf_layer.py. rbf_arch.py and rbf_kan.py are added.

• rbf_layer.py: introduces two layers, the pytorch Radial Basis Function Network Layer, and its adaptation to be used as RBF-KAN (also dubbed FastKAN, from ArXiv:2405.06721;
• rbf_arch.py introduces the RBF network Modulus Arc RBFArch. This fixes a small bug the stanrdard RBF implemention in Nvidia Modulus SYM has.
• rbf_kan.py: implements the RBFKANLayer to create the RBFKANArch for usange in Modulus Sym.

in examples there are avilable also the modulus exampple code for using (and testing) the two new architectures RBFArch and RBFKANLayer.

Examples

There are two PDE examples in the examples folder, Heat Equation and Burgers Equation.