Search results

A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or mathematical...

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...

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

Recurrent neural networks (RNNs) are a class of artificial neural networks for sequential data processing. Unlike feedforward neural networks, which process...

A neural network, also called a neuronal network, is an interconnected population of neurons (typically containing multiple neural circuits). Biological...

A feedforward neural network (FNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between...

Spiking neural networks (SNNs) are artificial neural networks (ANN) that more closely mimic natural neural networks. In addition to neuronal and synaptic...

A 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...

Quantum neural networks are computational neural network models which are based on the principles of quantum mechanics. The first ideas on quantum neural computation...

methods based on neural networks with representation learning. The adjective "deep" refers to the use of multiple layers in the network. Methods used can...

neural network in Wiktionary, the free dictionary. A neural network is an interconnected population of neurons: Neural network (biology), a network of...

A residual neural network (also referred to as a residual network or ResNet) is a deep learning architecture in which the weight layers learn residual...

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

In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function is an activation function defined as the...

Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. Their creation was inspired by neural circuitry...

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

physical neural network is a type of artificial neural network in which an electrically adjustable material is used to emulate the function of a neural synapse...

A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce...

A Siamese neural network (sometimes called a twin neural network) is an artificial neural network that uses the same weights while working in tandem on...

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