A 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...

in a network can perform complex tasks. There are two main types of neural networks. In neuroscience, a biological neural network is a physical structure...

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

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

Recurrent neural networks (RNNs) are a class of artificial neural networks designed for processing sequential data, such as text, speech, and time series...

An optical neural network is a physical implementation of an artificial neural network with optical components. Early optical neural networks used a photorefractive...

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...

physical structure of the neural network. Historically, the most common type of neural network software was intended for researching neural network structures...

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

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

Spiking neural networks (SNNs) are artificial neural networks (ANN) that mimic natural neural networks. These models leverage timing of discrete spikes...

Graph neural networks (GNN) are specialized artificial neural networks that are designed for tasks whose inputs are graphs. One prominent example is molecular...

"Cornell & NTT's Physical Neural Networks: A "Radical Alternative for Implementing Deep Neural Networks" That Enables Arbitrary Physical Systems Training"...

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

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

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...

subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation...

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

as Lisp machines, neuromorphic engineering, event cameras, and physical neural networks. Since 2017, several consumer grade CPUs and SoCs have on-die NPUs...

A neurally controlled animat is the conjunction of a cultured neuronal network a virtual or physical robotic body, the Animat, "living" in a virtual computer...

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

Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional computational...

A Hopfield network (or associative memory) is a form of recurrent neural network, or a spin glass system, that can serve as a content-addressable memory...

An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer (with typically...

Spatial neural networks (SNNs) constitute a supercategory of tailored neural networks (NNs) for representing and predicting geographic phenomena. They...

design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and...

intelligence that uses evolutionary algorithms to generate artificial neural networks (ANN), parameters, and rules. It is most commonly applied in artificial...

area networks (LAN), a common computer network installation. Any given node in the LAN has one or more physical links to other devices in the network; graphically...

cybernetics, quantitative psychology, machine learning, artificial neural networks, artificial intelligence and computational learning theory; although...

Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory...