Search results
Results from the WOW.Com Content Network
ELKI a software framework for development of data mining algorithms in Java. GAUSS, a matrix programming language for mathematics and statistics. GNU Data Language, a free compiler designed as a drop-in replacement for IDL. IDL, [21] a commercial interpreted language based on FORTRAN with some vectorization.
It is designed to follow the structure and workflow of NumPy as closely as possible and works with various existing frameworks such as TensorFlow and PyTorch. [5] [6] The primary functions of JAX are: [2] grad: automatic differentiation; jit: compilation; vmap: auto-vectorization; pmap: Single program, multiple data (SPMD) programming
FOSS statistics program, intended as an alternative to IBM SPSS Statistics. [Note 2] R: R Foundation 1997 1997 4.3.2 31 October 2023: Free GPL: Primarily for statistics, but there are many interfaces to open-source numerical software SageMath: William Stein: 2005 10.2 3 December 2023: Free GPL: Programmable, includes computer algebra, 2D+3D ...
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 ...
Simplified forms of Gaussian elimination have been developed for these situations. [ 6 ] The textbook Numerical Mathematics by Alfio Quarteroni , Sacco and Saleri, lists a modified version of the algorithm which avoids some of the divisions (using instead multiplications), which is beneficial on some computer architectures.
Random sample consensus (RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers, when outliers are to be accorded no influence [clarify] on the values of the estimates. Therefore, it also can be interpreted as an outlier detection method. [1]
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.
In this example, the Gauss–Newton algorithm will be used to fit a model to some data by minimizing the sum of squares of errors between the data and model's predictions. In a biology experiment studying the relation between substrate concentration [S] and reaction rate in an enzyme-mediated reaction, the data in the following table were obtained.