Neural network information

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...

Convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel)...

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

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

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...

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

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...

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...

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

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

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

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

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...

optical neural network (ONN) is a physical implementation of an artificial neural network with optical components. Biological neural networks are electrochemical...

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

A capsule neural network (CapsNet) is a machine learning system that is a type of artificial neural network (ANN) that can be used to better model hierarchical...

intelligence and machine learning applications, including artificial neural networks and machine vision. Typical applications include algorithms for robotics...

learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference...

developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's...

another to form large scale brain networks. Neural circuits have inspired the design of artificial neural networks, though there are significant differences...

artificial neural networks (ANNs), the neural tangent kernel (NTK) is a kernel that describes the evolution of deep artificial neural networks during their...