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🚀[FEA]: Add Kolmogorov - Arnold Networks for Modulus #494
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I am interested to do this. Is there a process to plan for it? Or should one just go and come back with a PR that assumes the API design (choice of arguments, etc) they like? PS. I see there is one available already: https://github.com/androbomb/kan-modulus |
Hi @androbomb, would you be interested in contributing your code here to Modulus? I'll be happy to work with you to get your PR merged. |
Dear @mnabian , I would love to. Let me know how to properly do it. Furthermore, I have started working on FastKAN implementation [see ArXiV paper], where instead of B-Splies, Jacobi/Chebyshev polinomials, a superposition of (learnable) Gaussian Kernels are used. Nevertheless, I must stress that the pure PyTorch implementations I used in my github are adaptation of others users code, as reported in the code and in the Readme.md:
Let me know how to proceed. |
Dear @mnabian , I updated my GitHub folder adding the code for FastKAN (KAN with Radial Basis Function instead of B-splines). In that repository I have created Modulus SYM models (not plain Modulus). Should I create a PR for Modulus SYM? Best regards |
Hi @androbomb, sorry I missed this thread. Yes please go ahead and open a PR. Feel free to add me as maintainer to your fork. |
Is this a new feature, an improvement, or a change to existing functionality?
New Feature
How would you describe the priority of this feature request
Low (would be nice)
Please provide a clear description of problem you would like to solve.
Due to its usefulness in Scientific Machine Learning, it would be relevant to add Kolmogorov - Arnold Network Layers in Modulus.
Describe any alternatives you have considered
No response
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