61,984 articles
Neural cellular automata
Neural cellular automata, or NCAs, are machine learning models in which a grid of cells is updated by a learned local rule, training patterns to grow and self-repair.
Neural collaborative filtering
Neural collaborative filtering (NCF) is a recommendation framework proposed in 2017 that replaces matrix factorization's dot product with a neural network that learns the user–item interaction function from implicit feedback.
Neural collapse
Neural collapse is a set of geometric regularities, named by Papyan, Han, and Donoho in 2020, that emerge in a deep network's last layer during terminal-phase training.
Neural DSP
Neural DSP, also known as Neural DSP Technologies, is the use of artificial neural networks for digital signal processing, most prominently neural-network digital predistortion that linearizes nonlinear wireless transmitters.
Neural field
A neural field, also known as an implicit neural representation or coordinate-based network, is a field parameterized by a neural network, popularized by NeRF in 2020 for novel view synthesis.
Neural gas
Neural gas is an unsupervised vector-quantization algorithm introduced by Thomas Martinetz and Klaus Schulten in 1991, in which prototype vectors adapt by a rank-based update rule like gas molecules distributing in a space.
Neural graph fingerprints
The neural graph fingerprint, often abbreviated NFP, is a learned, real-valued molecular fingerprint computed by a convolutional neural network directly on a molecule's graph, introduced by Duvenaud, Maclaurin, and colleagues in 2015.
Neural machine translation
Neural machine translation (NMT) is an approach that translates whole sentences using a neural network, first deployed in Google Translate in 2016 and now the dominant paradigm.
Neural mass model
A neural mass model is a computational model simulating the averaged activity of large neuron populations, the preferred approach to modeling EEG and MEG since the 1970s.
Neural network
A neural network, or artificial neural network (ANN), is a computational model of layered units whose weights are adjusted from data, now among the most used AI methods.
Neural network (machine learning)
A neural network, or artificial neural network, is a machine learning model built from layers of neurons whose weights are trained by backpropagation and stochastic gradient descent.
Neural network Gaussian process
A neural network Gaussian process is the Gaussian process reached as a Bayesian neural network's hidden units tend to infinity, first shown by Radford Neal in 1994.
Neural network quantization
Neural network quantization converts a model's weights and activations from floating-point numbers to low-bit integers, reducing memory, power, and latency; methods include post-training quantization and quantization-aware training.
Neural network verification
Neural network verification is the task of mathematically proving that a trained neural network satisfies a formal property, such as robustness, or producing a counterexample input when it fails.
Neural operators
Neural operators are neural network architectures that learn mappings between infinite-dimensional function spaces, formalized by Kovachki and Li in 2023 and used as fast surrogates for partial differential equation solvers.
Neural Ordinary Differential Equation
A neural ordinary differential equation, or neural ODE, is a neural network model whose hidden state evolves continuously and is computed by an ODE solver, introduced in 2018.
Neural Radiance Field
Neural Radiance Field, or NeRF, is a 2020 computer vision method that represents a 3D scene as a neural network to render photorealistic novel views.
Neural radiance fields
Neural radiance fields (NeRF) is a technique for synthesizing novel views of a scene from ordinary photographs, introduced by Ben Mildenhall and colleagues in March 2020.
Neural scaling law
A neural scaling law is an empirical mathematical relationship where a neural network's loss falls as a smooth power law as model size, training data, or compute increase.
Neural style transfer
Neural style transfer is a computer vision technique that renders one image in the artistic style of a second image, using features from a deep convolutional neural network.
Neural tangent kernel
The neural tangent kernel (NTK) is a kernel built from a network's output gradients, introduced by Jacot, Gabriel, and Hongler at NeurIPS 2018 to describe training in function space.
Neural text-to-speech synthesis
Neural text-to-speech synthesis is the family of deep-learning methods that converts written text into natural spoken audio, replacing rule-based systems with neural networks trained on text-and-audio pairs, from WaveNet to zero-shot voice cloning.
NeuralGCM
NeuralGCM (Neural General Circulation Models) is a hybrid weather and climate model combining physics with machine learning, developed by Google Research and published in Nature in 2024.
Neurath Power Station
Neurath Power Station (Kraftwerk Neurath) is a lignite-fired power station at Grevenbroich-Neurath, Germany, owned by RWE Power, whose two 1,100-MW units are the world's most powerful lignite-fired units.
Neuro (gum)
Neuro is a sugar-free energy and focus gum delivering 40 mg caffeine plus L-theanine and B vitamins per piece, founded in 2015 by Kent Yoshimura and Ryan Chen.
Neuro-symbolic AI
Neuro-symbolic AI, also written neurosymbolic AI or NeSy, is the subfield of artificial intelligence that combines neural-network machine learning with symbolic knowledge representation and reasoning.
Neuroevolution
Neuroevolution is a machine learning approach that uses evolutionary algorithms to optimize neural networks, maintaining a population of candidate networks rather than training weights by gradient descent.
Neuroevolution of augmenting topologies
Neuroevolution of augmenting topologies (NEAT) is an evolutionary algorithm introduced by Kenneth Stanley and Risto Miikkulainen in 2002 that evolves both neural network weights and structure, growing from minimal networks.
NeuroLogica
NeuroLogica is a medical imaging company founded in 2004 in Danvers, Massachusetts, best known for the portable CereTom head scanner and BodyTom full-body scanner, acquired by Samsung in 2013.
NeuroML
NeuroML (Neural Open Markup Language) is an XML-based, simulator-independent language for describing models of neuronal cells and networks, first proposed in 2001 and now an INCF-endorsed standard.