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29 de jun. de 2024 · Hay un nuevo periódico en la ciudad llamado “Red Kolmogorov-Arnold”, o KAN para abreviar, que desafía a los MLP. Si la solución que proponen realmente escala, entonces podremos tener la próxima generación de redes neuronales, lo que nos acercará un paso más a la Inteligencia General Artificial (AGI).
13 de jun. de 2024 · Here’s Kolmogorov-Arnold Networks (KANs), a new approach to neural networks inspired by the Kolmogorov-Arnold representation theorem. Unlike traditional MLPs, which use fixed activation functions at each neuron, KANs use learnable activation functions on the edges (weights) of the network.
10 de jun. de 2024 · We introduce Graph Kolmogorov-Arnold Networks (GKAN), an innovative neural network architecture that extends the principles of the recently proposed Kolmogorov-Arnold Networks (KAN) to graph-structured data.
Hace 6 días · A group of researchers proposed Kolmogorov–Arnold Networks (KAN) reporting better accuracy and interpretability than MLP in certain tasks. How can it improve the results achieved by the fundamental MLP?
17 de jun. de 2024 · KAN aims to provide a more efficient and interpretable approach to universal function approximation compared to traditional deep neural networks. The paper introduces the KAN architecture, analyzes its theoretical properties, and demonstrates its performance on various benchmark tasks.
13 de jun. de 2024 · Kolmogorov-Arnold Networks (KANs) introduce a paradigm of neural modeling that implements learnable functions on the edges of the networks, diverging from the traditional node-centric activations in neural networks.
