In general, a function approximation problem asks us to select a function among a well-defined class[citation needed][clarification needed] that closely...

universal approximation theorems state that neural networks with a certain structure can, in principle, approximate any continuous function to any desired...

mathematics, Stirling's approximation (or Stirling's formula) is an asymptotic approximation for factorials. It is a good approximation, leading to accurate...

o'clock). Although approximation is most often applied to numbers, it is also frequently applied to such things as mathematical functions, shapes, and physical...

mathematics, a Padé approximant is the "best" approximation of a function near a specific point by a rational function of given order. Under this technique, the...

In calculus, Taylor's theorem gives an approximation of a k {\textstyle k} -times differentiable function around a given point by a polynomial of degree...

of admissible solutions, increasing the generalizability of the function approximation. This way, embedding this prior information into a neural network...

squares function approximation applies the principle of least squares to function approximation, by means of a weighted sum of other functions. The best...

powerful: the use of samples to optimize performance, and the use of function approximation to deal with large environments. Thanks to these two key components...

have been a number of approximations for the exponential integral function. These include: The Swamee and Ohija approximation E 1 ( x ) = ( A − 7.7 +...

relative error to about 0.00013. This approximation can be inverted to obtain an approximation for the inverse error function: erf − 1 ⁡ ( x ) ≈ sgn ⁡ x ⋅ (...

mathematics, a linear approximation is an approximation of a general function using a linear function (more precisely, an affine function). They are widely...

In mathematics, approximation theory is concerned with how functions can best be approximated with simpler functions, and with quantitatively characterizing...

proven to be a universal function approximator. This is known as the Universal Approximation Theorem. The identity activation function does not satisfy this...

combination with (linear) function approximation. The advantage of Greedy GQ is that convergence is guaranteed even when function approximation is used to estimate...

of that function for an intermediate value of the independent variable. A closely related problem is the approximation of a complicated function by a simple...

values of functions which cannot be computed directly, but only estimated via noisy observations. In a nutshell, stochastic approximation algorithms...

radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including function approximation, time series...

for N much larger than n, the binomial distribution remains a good approximation, and is widely used. If the random variable X follows the binomial distribution...

response to chemical signals. For a smooth approximation to the step function, one can use the logistic function H ( x ) ≈ 1 2 + 1 2 tanh ⁡ k x = 1 1 + e...

In mathematical analysis, the Weierstrass approximation theorem states that every continuous function defined on a closed interval [a, b] can be uniformly...

expansion used in the approximation. The expressions: a zeroth-order approximation, a first-order approximation, a second-order approximation, and so forth are...

a function approximation problem asks us to select a function among a well-defined class that closely matches ("approximates") a target function in a...

is called the nth Taylor polynomial of the function. Taylor polynomials are approximations of a function, which become generally more accurate as n increases...

Pseudogamma function Hadamard's gamma function Inverse gamma function Lanczos approximation Multiple gamma function Multivariate gamma function p-adic gamma...

W function by piecewise minimax rational function approximation with variable transformation". doi:10.13140/RG.2.2.30264.37128. "Lambert W Functions -...

basis vectors. In numerical analysis and approximation theory, basis functions are also called blending functions, because of their use in interpolation:...

 259. ISBN 0126077444. Christian Schüller (2006). "§2.4.1 Envelope function approximation (EFA)". Inelastic Light Scattering of Semiconductor Nanostructures:...

and molecular physics, the Born–Oppenheimer (BO) approximation is the assumption that the wave functions of atomic nuclei and electrons in a molecule can...

In mathematics, the Lanczos approximation is a method for computing the gamma function numerically, published by Cornelius Lanczos in 1964. It is a practical...