The Kolmogorov–Arnold Networks (KAN) are gaining attention for their potential benefits over Multi-Layer Perceptrons in scientific function modeling and human activity recognition. KANs have shown superior performance in feature extraction tasks and solving PDEs. They also address the issue of 'Catastrophic forgetting' in machine learning, presenting a promising alternative to convolutional neural networks.
🔥Convolutional Kolmogorov-Arnold Networks Preprint out now🔥 I'm very excited to release our preprint on Arxiv. Also, my first paper. We proposed a novel architecture that shows potential to compete with CNNs. Want to learn more about it? 🧵Follow this thread👇 https://t.co/P8ObSpnPqX
This is a huge power of of the Kolmogorov-Arnold Networks (KAN) - "Catastrophic forgetting" can be SOLVED with KAN 🔥 An excerpt from the paper: "KAN: Kolmogorov–Arnold Networks" "Catastrophic forgetting is a serious problem in current machine learning. When a human masters a… https://t.co/PpHOJBrD8s
Kolmogorov Arnold Network” is one of the best innovations of 2024. “Kolmogorov–Arnold-Informed neural network: A physics-informed deep learning framework for solving PDEs based on Kolmogorov–Arnold Networks” “Our results demonstrate that KINN significantly outperforms MLP in… https://t.co/pGFlx83YwG
With #KAN you can. “BSRBF-KAN: A COMBINATION OF B-SPLINES AND RADIAL BASIS FUNCTIONS IN KOLMOGOROV-ARNOLD NETWORKS” complete with code 🧑💻 “In this paper, we introduce BSRBF-KAN, a Kolmogorov Arnold Network (KAN) that combines Bsplines and radial basis functions (RBFs) to fit… https://t.co/f7h7LIGPCU
With #KAN you can. Kolmogorov-Arnold Networks outperform convolutional neural networks on feature extraction task for human activity recognition. 🔥🔥🔥🔥🔥 “Initial Investigation of Kolmogorov-Arnold Networks (KANs) as Feature Extractors for IMU Based Human Activity… https://t.co/Ax3pc8hJ4e
Kolmogorov–Arnold Networks: Hype or Deep Learning Revolution? by @Machine01776819 https://t.co/yILwebzRwu
Much has been made about the Kolmogorov–Arnold Networks and their potential advantages over Multi-Layer Perceptrons, especially for modeling scientific functions. https://t.co/cgyjgrLmIu