Showing Items 301310 of 537 on page 31 of 54: First Previous 26 27 28 29 30 31 32 33 34 35 36 Next Last
About: This is a set of MATLAB(R) functions and MEX files which I wrote to make working with this system somewhat bearable. They allow to call BLAS and LAPACK functions, which do very efficient dense [...] Changes:Initial Announcement on mloss.org.

About: You should never compute, maintain, or update the inverse of a symmetric positive definite matrix if you do not have to. Computing the inverse or manipulating it is inherently instable. You can [...] Changes:Initial Announcement on mloss.org.

About: You can use the software in this package to efficiently sample from Changes:Initial Announcement on mloss.org.

About: GPUML is a library that provides a C/C++ and MATLAB interface for speeding up the computation of the weighted kernel summation and kernel matrix construction on GPU. These computations occur commonly in several machine learning algorithms like kernel density estimation, kernel regression, kernel PCA, etc. Changes:Initial Announcement on mloss.org.

About: HDDM is a python toolbox for hierarchical Bayesian parameter estimation of the Drift Diffusion Model (via PyMC). Drift Diffusion Models are used widely in psychology and cognitive neuroscience to study decision making. Changes:

About: Orthonormal wavelet transform for D dimensional tensors in L levels. Generic quadrature mirror filters and tensor sizes. Runtime is O(n), plain C, MEXwrapper and demo provided. Changes:Initial Announcement on mloss.org. 
About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications. Changes:

About: OXlearn is a free neural network simulation software that enables you to build, train, test and analyse connectionist neural network models. Because OXlearn is implemented as a Matlab toolbox you can run it on all operation systems (Windows, Linux, MAC, etc.), and there is a compiled version for XP. Changes:Initial Announcement on mloss.org.

About: Classification and Regression Training LSF Style: Augment some caret functions for parallel processing Changes:Initial Announcement on mloss.org.
