In computing, the network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function...

Internet Protocol (IP). Early versions of this networking model were known as the Department of Defense (DoD) model because the research and development were...

A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a...

Hopfield network (associative memory or Ising–Lenz–Little model or Nakano-Amari-Hopfield network) is a spin glass system used to model neural networks, based...

OSI reference model, the communications between systems are split into seven different abstraction layers: Physical, Data Link, Network, Transport, Session...

The Gaussian network model (GNM) is a representation of a biological macromolecule as an elastic mass-and-spring network to study, understand, and characterize...

Hierarchical network models are iterative algorithms for creating networks which are able to reproduce the unique properties of the scale-free topology...

The network model is a database model. The term may also refer to: Network topology Packet generation model Channel model This disambiguation page lists...

steps). The intent of the transformer model is to take a seq2seq model and remove its recurrent neural networks, but preserve its additive attention mechanism...

knowing whether a network is scale-free according to statistically rigorous definitions. Preferential attachment and the fitness model have been proposed...

Metabolic network modelling, also known as metabolic network reconstruction or metabolic pathway analysis, allows for an in-depth insight into the molecular...

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...

of recurrent neural network models in neuroscience. Two early influential works were the Jordan network (1986) and the Elman network (1990), which applied...

article is a comprehensive view of modeling a neural network (technically neuronal network based on neuron model). Once an approach based on the perspective...

Network model Relational model Entity–relationship model Enhanced entity–relationship model Object model Document model Entity–attribute–value model Star...

to model reverse logistics network from an economics point of view, the following simplified reverse logistics system has to be set. In this model the...

may be identical. A network's physical topology is a particular concern of the physical layer of the OSI model. Examples of network topologies are found...

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

of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena." The study of networks has...

Copying network models are network generation models that use a copying mechanism to form a network, by repeatedly duplicating and mutating existing nodes...

geometry models of wireless networks refer to mathematical models based on stochastic geometry that are designed to represent aspects of wireless networks. The...

star network network topology. "Hubbing" involves "the arrangement of a transportation network as a hub-and-spoke model". The hub-and-spoke model, as compared...

model Hierarchical model Network model Relational model Concept-oriented model Star schema A data structure diagram (DSD) is a diagram and data model...

Internet Protocol Suite (TCP/IP) and other models and they often do not fit neatly into OSI layers. Telephone network modems IrDA physical layer USB physical...

The Barabási–Albert (BA) model is an algorithm for generating random scale-free networks using a preferential attachment mechanism. Several natural and...

three networks in the so-called triple-network model, along with the salience network and the default mode network (DMN). The salience network facilitates...

calculated by comparing clustering and path length of a given network to an Erdős–Rényi model with same degree on average. σ = C C r L L r {\displaystyle...

In the seven-layer OSI model of computer networking, the network layer is layer 3. The network layer is responsible for packet forwarding including routing...

time. Neural Network Models can undergo learning patterns to use episodic memories to predict certain moments. Neural network models help the episodic memories...