GitHub5 天
Activation Functions Understanding in Neural Networks.md
Neural networks utilize activation functions to transform input signals into output activations, introducing essential non-linearity that enables the network to learn complex patterns. This ...
GitHub5 天
Activation Functions The Driving Force of Neural Networks.md
Cross Beat (xbe.at) - Your hub for python, machine learning and AI tutorials. Explore Python tutorials, AI insights, and more. - 4lexLammers/Machine-Learning-full ...
What is a Neural Network?
Recurrent Neural Networks (RNN): A special type of neural network, RNN is a complex network that uses the output of a node ...
Frontiers5 天
Physics-Informed Neural Networks for Cardiac Activation Mapping
A critical procedure in diagnosing atrial fibrillation is the creation of electro-anatomic activation maps. Current methods generate these mappings from interpolation using a few sparse data points ...
Frontiers21 天
SineKAN: Kolmogorov-Arnold Networks using sinusoidal activation functions
Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation ...
Neural pathway in mice sheds light on how the brain regulates learned immune responses
The brain of humans and other animals is known to contribute to the protection of the body from infections. Past studies have unveiled the existence of the so-called conditioned immune response (CIR), ...