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  2. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy addresses the slowness problem partly by providing multidimensional arrays and functions and operators that operate efficiently on arrays; using these requires rewriting some code, mostly inner loops, using NumPy. Using NumPy in Python gives functionality comparable to MATLAB since they are both interpreted, [18] and they both allow the ...

  3. Gaussian random field - Wikipedia

    en.wikipedia.org/wiki/Gaussian_random_field

    One way of constructing a GRF is by assuming that the field is the sum of a large number of plane, cylindrical or spherical waves with uniformly distributed random phase. Where applicable, the central limit theorem dictates that at any point, the sum of these individual plane-wave contributions will exhibit a Gaussian distribution.

  4. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    Mathematically, the derivatives of the Gaussian function can be represented using Hermite functions. For unit variance, the n-th derivative of the Gaussian is the Gaussian function itself multiplied by the n-th Hermite polynomial, up to scale. Consequently, Gaussian functions are also associated with the vacuum state in quantum field theory.

  5. Diamond-square algorithm - Wikipedia

    en.wikipedia.org/wiki/Diamond-square_algorithm

    The square step: For each diamond in the array, set the midpoint of that diamond to be the average of the four corner points plus a random value. Each random value is multiplied by a scale constant, which decreases with each iteration by a factor of 2 −h, where h is a value between 0.0 and 1.0 (lower values produce rougher terrain). [2]

  6. Gaussian process - Wikipedia

    en.wikipedia.org/wiki/Gaussian_process

    A Gaussian process can be used as a prior probability distribution over functions in Bayesian inference. [7] [23] Given any set of N points in the desired domain of your functions, take a multivariate Gaussian whose covariance matrix parameter is the Gram matrix of your N points with some desired kernel, and sample from that Gaussian. For ...

  7. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    A random element h ∈ H is said to be normal if for any constant a ∈ H the scalar product (a, h) has a (univariate) normal distribution. The variance structure of such Gaussian random element can be described in terms of the linear covariance operator K: H → H. Several Gaussian processes became popular enough to have their own names ...

  8. Musk's X ineffective against surge in US election ... - AOL

    www.aol.com/news/musks-x-ineffective-against...

    Of the 283 misleading X posts that CCDH analyzed, 209, or 74% of the posts, did not show accurate notes to all X users correcting false and misleading claims about the elections, the report said.

  9. Gauss–Legendre quadrature - Wikipedia

    en.wikipedia.org/wiki/Gauss–Legendre_quadrature

    Gauss–Legendre quadrature is optimal in a very narrow sense for computing integrals of a function f over [−1, 1], since no other quadrature rule integrates all degree 2n − 1 polynomials exactly when using n sample points. However, this measure of accuracy is not generally a very useful one---polynomials are very simple to integrate and ...

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