KAN: Kolmogorov-Arnold Networks Paper Explained

#kan #mlp #deeplearning #machinelearning #ai
In this video, I explained the recent research study that is Kolmogorov-Arnold representation theorem.
The KAN is an approach in the field of machine learning that is based on the Kolmogorov-Arnold representation theorem from mathematical analysis. This method applies the theorem's insights to build predictive models for complex, high-dimensional datasets. KAN uses the idea that any multivariate function can be decomposed into sums and compositions of univariate functions.
Full access of the paper: arxiv.org/html/2404.19756v1/
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⏱️ Timestamps
0:00 Intro
0:23 KAN Kolmogorov-Arnold Networks intro
1:04 Basics of MLP
1:56 Explained MLP approach presented in the paper
3:00 Explained KAN approach presented in the paper
4:18 KAN defined
6:13 symbolic regression with KAN
8:21 Accuracy
10:33 Interpretability
11:28 Should we use KAN or MLP?

[@ashwinkumar5223]

Thank you.. Well said.

[@time-barbaad]

Please implement it also.

[@airesearcher24]

Definitely, I am going to create a video on the KAN implementation.. Thanks 👍

[@umair_thakur]

Hello Ma'am, can you please make a video for people who want to become an AI Researcher and also share what an AI Researcher does, your personal experiences while working as an AI researcher, etc. Would be really be a good learning for beginners

[@airesearcher24]

Certainly, I will make an informative video on the topic.. Thanks for the suggestion 👍

[@competitivestudyhub1505]

Thanks for uploading such an amazing video ma'am I would like to make career in A.I.

[@airesearcher24]

Thanks.. keep watching 👍