Hybrid neural network information

hybrid neural network can have two meanings: Biological neural networks interacting with artificial neuronal models, and Artificial neural networks with...

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...

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 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...

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

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

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

neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy...

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

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

In artificial intelligence, a differentiable neural computer (DNC) is a memory augmented neural network architecture (MANN), which is typically (but not...

Bidirectional recurrent neural networks (BRNN) connect two hidden layers of opposite directions to the same output. With this form of generative deep...

20 January 2015. Morgan, Bourlard, Renals, Cohen, Franco (1993) "Hybrid neural network/hidden Markov model systems for continuous speech recognition. ICASSP/IJPRAI"...

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...

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

Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence...

neural networks Long short-term memory Hopfield networks Attractor networks Deep learning Hybrid neural network Learning algorithms for neural networks Hebbian...

recognition. Between the 1980s and 1990s, hybrid intelligence systems merged fuzzy logic, neural networks, and evolutionary computation that solved complicated...

Neuro-fuzzy systems Hybrid connectionist-symbolic models Fuzzy expert systems Connectionist expert systems Evolutionary neural networks Genetic fuzzy systems...

research in the fields of computational psychology and hybrid connectionist neural network (i.e., neural symbolic models). In particular, he applied these...

IEEE Transactions on Neural Networks and Learning Systems is a monthly peer-reviewed scientific journal published by the IEEE Computational Intelligence...

where a small portion of the data is tagged, and Self Supervision. Neural network tasks are often categorized as discriminative (recognition) or generative...

Grefenstette, Edward; Ramalho, Tiago (12 October 2016). "Hybrid computing using a neural network with dynamic external memory". Nature. 538 (7626): 471–476...