A modular neural network is an artificial neural network characterized by a series of independent neural networks moderated by some intermediary. Each...

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

Modularity is a measure of the structure of networks or graphs which measures the strength of division of a network into modules (also called groups,...

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

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

represents a scene as a radiance field parametrized by a deep neural network (DNN). The network predicts a volume density and view-dependent emitted radiance...

multiplicative units. Neural networks using multiplicative units were later called sigma-pi networks or higher-order networks. LSTM became the standard...

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

Encodings Investigating the Evolution of Modular Neural Networks Evolving Objects that can be 3D-printed Evolving the Neural Geometry and Plasticity of an ANN...

NeuroSolutions is a neural network development environment developed by NeuroDimension. It combines a modular, icon-based (component-based) network design interface...

Traditional deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), excel in processing data on regular grids...

with strong acceleration via graphics processing units (GPU) Deep neural networks built on a tape-based automatic differentiation system In 2001, Torch...

Time delay neural network (TDNN) is a multilayer artificial neural network architecture whose purpose is to 1) classify patterns with shift-invariance...

striate cortex which contains thousands of modules that are part of modular neural networks. The neurons in the striate cortex send axons to the extrastriate...

Modularity of mind is the notion that a mind may, at least in part, be composed of innate neural structures or mental modules which have distinct, established...

complex networks, modularity is a benefit function that measures the quality of a division of a network into groups or communities. In modular programming...

Distributed Processing (PDP)), Biological neural network, Artificial neural network (a.k.a. Neural network), Computational neuroscience, as well as in...

"The Formation of Synchronization Cliques During Development of Modular Neural Networks". Fuchs, E., Ayali, A., Boccaletti, S., ., Ben-Jacob, E., Physical...

relatively shallow models, grokking has been observed in deep neural networks and non-neural models and is the subject of active research. One potential...

Confidence Propagation Neural Network (BCPNN) is an artificial neural network inspired by Bayes' theorem, which regards neural computation and processing...

optimization of modularity as the algorithm progresses. Modularity is a scale value between −1 (non-modular clustering) and 1 (fully modular clustering) that...

connectomics and network neuroscience, have found the small-worldness of neural networks to be associated with efficient communication. In neural networks, short...

Modularity refers to the ability of a system to organize discrete, individual units that can overall increase the efficiency of network activity and,...

Neuroplasticity, also known as neural plasticity or just plasticity, is the ability of neural networks in the brain to change through growth and reorganization...

They considered neural networks that operate in discrete steps of time t = 0 , 1 , … {\displaystyle t=0,1,\dots } . The neural network contains a number...

example being the neural network. A further design issue is additionally a decision between holistic and atomistic, or (more concretely) modular structure. In...

science) Repertory grid Semantic lexicon Semantic similarity network Semantic neural network SemEval – an ongoing series of evaluations of computational...

write() methods. The nn package is used for building neural networks. It is divided into modular objects that share a common Module interface. Modules...

Designed to enable fast experimentation with deep neural networks, Keras focuses on being user-friendly, modular, and extensible. It was developed as part of...

A computer network is a collection of communicating computers and other devices, such as printers and smart phones. In order to communicate, the computers...