Explore: Gaussian Process

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

Kriging (/ˈkriːɡɪŋ/), also known as Gaussian process regression, is a method of interpolation based on Gaussian process governed by prior covariances. Under

In signal processing theory, Gaussian noise, named after Carl Friedrich Gauss, is a kind of signal noise that has a probability density function (pdf)

of statistical analysis software that allows doing inference with Gaussian processes often using approximations. This article is written from the point

A Neural Network Gaussian Process (NNGP) is a Gaussian process (GP) obtained as the limit of a certain type of sequence of neural networks. Specifically

Finite-dimensional distribution First passage time Galton–Watson process Gamma process Gaussian process – a process where all linear combinations of coordinates are normally

Additive white Gaussian noise (AWGN) is a basic noise model used in information theory to mimic the effect of many random processes that occur in nature

A one-dimensional GRF is also called a Gaussian process. An important special case of a GRF is the Gaussian free field. With regard to applications of

computer hours [3]. The typical model for a computer code output is a Gaussian process. For notational simplicity, assume f ( x ) {\displaystyle f(x)} is

constant. Gaussian process is a powerful non-linear interpolation tool. Many popular interpolation tools are actually equivalent to particular Gaussian processes