Search Results for "artificial intelligence algorithm"

* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive...

newLISP for BSDs, LINUX, MacOS X, SunOS and Win32: small, fast 350+ functions, a -C-, MySQL, PostgreSQL, SQLite, ODBC, TCP/IP, UDP, XML, Java interface, string processing, regular expressions , math, financial, statistical functions, Win32 DLL

A multi-platform collection of C++ software libraries for Computer Vision and Image Understanding.

Bayesian Network tools in Java (BNJ) is an open-source suite of software tools for research and development using graphical models of probability. It is published by the Kansas State University Laboratory for Knowledge Discovery in Databases (KDD).

This project has been moved to bitbucket.org: - https://bitbucket.org/vahidi/jbdd/wiki/Home - https://bitbucket.org/vahidi/jdd/wiki/Home It includes two libraries for working with decision diagrams: - JBDD: a Java interface to two popular BDD libraries, CUDD and BuDDy - JDD: a native Java library supporting BDD, Z-BDD

BabyTALK is to add another brick in the wall of natural languages learning. The baby needs to structure a corpus of texts when his tutor points and talks about a particular part of the corpus. The baby is also to describe any selected part of the corpus.

RealPaver is a modeling language for solving mixed-integer nonlinear constraint systems.

Java/XML toolkit for research using Bayesian networks and other graphical models of probability (exact and approximate inference, structure learning, etc.)

Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.