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 ...
Frontiers22 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 ...
C&EN14 天
Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks
Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan Taiwan International Graduate Program on Sustainable Chemical Science and ...