Explore: Neural Nets

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

A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep

model of a biological neuron in a neural network. The artificial neuron is the elementary unit of an artificial neural network. The design of the artificial

Physics-informed neural networks (PINNs), also referred to as Theory-Trained Neural Networks (TTNs), are a type of universal function approximators that

Jürgen (21 September 2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation. 22 (12): 3207–3220. arXiv:1003.0358

functions for artificial neural networks, and finds application in computer vision and speech recognition using deep neural nets and computational neuroscience

attempt to find a quantum equivalent for the perceptron unit from which neural nets are constructed. A problem is that nonlinear activation functions do

NBS where he developed the Cerebellar Model Arithmetic Computer (CMAC) neural net model. From June 1980 to January 1981 he was leader of the Programmable

contrasts recursive solutions with neural nets, he likes both but specifically mentions how valuable neural nets are since they destroy information during

A Self-Organizing Neural Network Model for a Mechanism of Visual Pattern Recognition". Competition and Cooperation in Neural Nets. In Competition and