💡 Words with a Similar Meaning to "Graph neural network"
Found via reverse dictionary — words that share a conceptual meaning.
| Word | Definition |
|---|---|
| recurrent neural networknoun | (machine learning) An artificial neural network where the connections between units give them a kind of internal memory useful for processing arbitrary sequences of inputs as in speech recognition. |
| probabilistic neural network | A probabilistic neural network is a feedforward neural network, which is widely used in classification and pattern recognition problems. |
| activation functionnoun | (computer science) A function that defines the output of a particular node in an artificial neural network on the basis of its inputs. |
| graph statenoun | (physics) Any of a class of multipartite entangled quantum states that can be interpreted using the mathematics of graph theory |
| knowledge graphnoun | (information science) A knowledge base with an interlinked graph structure. |
| graphnoun | (applied mathematics, statistics) A data chart (graphical representation of data) intended to illustrate the relationship between a set (or sets) of numbers (quantities, measurements or indicative numbers) and a reference set, whose elements are indexed to those of the former set(s) and may or may not be numbers. |
| artificial neuron | alt=Artificial neuron structure|thumb|306x306px|Artificial neuron structure |
| radial basis function network | In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. |
| general regression neural network | Generalized regression neural network is a variation to radial basis neural networks. |
| graph theorynoun | (uncountable, mathematics) The branch of mathematics dealing with the properties of graphs (networks of vertices and edges). |
| algebraic graph theorynoun | (uncountable, mathematics, graph theory) The subbranch of graph theory in which algebraic methods are applied to problems about graphs. |
| bayesian networknoun | (statistics) A directed acyclic graph whose vertices represent random variables and whose directed edges represent conditional dependencies. Each random variable can fall into any of at least two mutually disjoint states, and has a probability function which takes as inputs the states of its parent nodes and returns as output the probability of being in a certain state for a given combination of the states of its parent nodes. A node without parent nodes just has an unconditioned probability of being in some given state. |
| quantum neural network | Quantum neural networks are computational neural network models which are based on the principles of quantum mechanics. |
| adjacency matrixnoun | (graph theory) A matrix showing which vertices of a graph are adjacent to which other vertices. |
| network theory | In mathematics, computer science and network science, network theory is a part of graph theory. |
| graphical model | A graphical model or probabilistic graphical model or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. |
| adjacency listnoun | (mathematics) A collection of unordered lists (each representing the neighbours of a vertex) that represents a finite graph. |
| social network analysis | the process of investigating social structures through the use of networks and graph theory. |
| deep belief network | In machine learning, a deep belief network is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of latent variables ("hidden units"), with connections between the layers but not between units within each layer. |
| phylogenetic network | — |
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