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imaging science, difference of Gaussians (DoG) is a feature enhancement algorithm that involves the subtraction of one Gaussian blurred version of an original...

convolving the image with the Laplacian of the Gaussian function, or, as a fast approximation by difference of Gaussians. Then, zero crossings are detected in...

Gaussian integers and polynomials of one variable. This led to modern abstract algebraic notions such as Euclidean domains. The Euclidean algorithm calculates...

fairly accurate approximations of π for practical computations. Around 250 BC, the Greek mathematician Archimedes created an algorithm to approximate π...

In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued...

machine learning, Gaussian process approximation is a computational method that accelerates inference tasks in the context of a Gaussian process model, most...

{\displaystyle n} point Gaussian quadrature ( ξ , w ) {\displaystyle (\xi ,w)} rule then results in the following approximation: ∫ a b f ( x ) d x ≈ b...

example, to estimate a mixture of gaussians, or to solve the multiple linear regression problem. The EM algorithm was explained and given its name in...

In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that...

processing, a Gaussian filter is a filter whose impulse response is a Gaussian function (or an approximation to it, since a true Gaussian response would...

energy approximation, and satisfiability. The algorithm was first proposed by Judea Pearl in 1982, who formulated it as an exact inference algorithm on trees...

theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional...

heuristic algorithms converge quickly to a local optimum. These are usually similar to the expectation–maximization algorithm for mixtures of Gaussian distributions...

Spigot algorithm — algorithms that can compute individual digits of a real number Approximations of π: Liu Hui's π algorithm — first algorithm that can...

Karagiannidis, G. K.; Lioumpas, A. S. (2007). "An improved approximation for the Gaussian Q-function" (PDF). IEEE Communications Letters. 11 (8): 644–646...

In mathematics, low-rank approximation refers to the process of approximating a given matrix by a matrix of lower rank. More precisely, it is a minimization...

Laplace's approximation provides an analytical expression for a posterior probability distribution by fitting a Gaussian distribution with a mean equal...

object under usual illumination. Gaussian smoothing is also used as a pre-processing stage in computer vision algorithms in order to enhance image structures...

applying the Gaussian copula to credit derivatives to be one of the causes of the 2008 financial crisis; see David X. Li § CDOs and Gaussian copula. Despite...

quasi-Newton methods like BFGS, is an algorithm of an iterative method or a method of successive approximation. An iterative method is called convergent...