Generalized regression neural network (GRNN) is a variation to radial basis neural networks. GRNN was suggested by D.F. Specht in 1991. GRNN can be used...

types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate...

descent to minimize least-square loss for neural networks yields the same mean estimator as ridgeless kernel regression with the NTK. This duality enables simple...

A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization...

graph neural network (GNN) belongs to a class of artificial neural networks for processing data that can be represented as graphs. In the more general subject...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function...

arbitrarily deep neural networks was published by Alexey Ivakhnenko and Lapa in 1967, which they regarded as a form of polynomial regression, or a generalization...

Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural...

A probabilistic neural network (PNN) is a feedforward neural network, which is widely used in classification and pattern recognition problems. In the PNN...

function network (RBF) General regression neural network (GRNN) Probabilistic neural network (PNN) Self-organizing map (SOM) Time-lag recurrent network (TLRN)...