Search Results for "mixture"

* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:...

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

TPLS is a powerful and efficient 3D Direct Numerical Simulation (DNS) flow solver to simulate multiphase flows at unprecedented detail, speed and accuracy. This flow solver has been developed by Lennon Ó Náraigh (Mathematical Sciences, University College Dublin), Prashant Valluri (Engineering, University of Edinburgh), David Scott, Toni Collis and Iain Bethune (EPCC at the University of Edinburgh) and Peter Spelt (Université de Lyon1, Claude Bernard) under the aegis of several HECToR /...

...fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147

GenoTan identifies inherited variation of microsatellite loci from short sequence reads using a discretized Gaussian mixture model combined with a rules-based approach.

The AK toolkit is another kit for building and use Hidden Markov Models (HMMs). Originally developed for handwritten text recognition (HTR) using Bernoulli HMMs, it also implements diagonal Gaussians and can be used for any other purpose.

Matlab plug-in for SPM allowing to obtain a threshold for cluster FDR - the method fits a Gamma-Gaussian mixture model to the SPM-T and finds the optimal threshold (crossing between noise and activation). Optionally write the thresholded maps.

SNOMP (SNOMP is Not OpenMP) is a library for semi-shared memory parallelization.

ESMERALDA is a development environment for statistical recognizers operating on sequential data (speech, handwriting, biological sequences). It supports continuous density Hidden Markov models, Markov chain (N-gramm) models, and Gaussian mixture models.

This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.

GMM-GMR is a light package of functions in C/C++ to compute Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR). It allows to encode any dataset in a GMM, and GMR can then be used to retrieve partial data by specifying the desired inputs.

clusterviz allows to cluster three-dimensional data. The clustering process is visualized using OpenGL. As clustering algorithms the family of k-means algorithms is implemented, including mixture models.

A straight-forward Java implementation of a mixture model with pluggable mixture functions, e.g. a mixture of Gaussian functions. The number and dimensionality of the mixture functions is not limited. All critical calculations are performed in log-space.