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neuralnetgen is intended to be a universal neural net generator that receives a neural net description (on Neural Net Description Language, also developed on this project) and generates ANSI C code of a library that implements it.
REPCAL (REverse Polish CALculator) is a light and fast calculator in RPN (reverse polish notation) mode for the console (command line). It is written in 180 lines of Python code, and can be used both interactively or inside shell scripts.
The General Intensional Programming System (GIPSY) consists in three modular sub-systems: The General Intensional Programming Language Compiler (GIPC) ; the General Eduction Engine (GEE), and the Intensional Run-time Programming Environment (RIPE).
mupacs is a lisp mode for editing MuPAD code (automatic indentation, fontification, ...), as well as running MuPAD in a subshell, with support for debugger and online documentation
Accurately convert voice to text in over 125 languages and variants by applying powerful machine learning models with an easy-to-use API.
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Numerically estimate an efficiency of code construction algorithms. Randomly generate n binary words of length m with minimum Hamming distance d and create a prefix code (= retrieval tree) from them. Based on PhD work.
"CAGE", the Computer Audio Garden in Eclipse, is to be an Eclipse-based, Java and XML workbench, for the computer music composer. It will use the Rich Client Platform to provide a basic backbone framework, enabling existing computer music tools to be p
Active Networking provides a framework in which executable code within data packets can execute upon intermediate network nodes. The goal of this research is to develop active networks that are capable of predicting their own behavior and to use this ca
kin is a set of libraries and tools supporting meta-programming for engineering and technical computing applications. This JVM version of kin has been superseded by the stand-alone version being developed at http://purl.org/net/kin.
SymDiff is a little command line tool for symbolic differentiation and expression evaluation. Furthermore, the code can be used for the symbolical implementation of certain mathematical algorithms that require derivatives.
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Emily is a friendly name for the Machine Learning Environment (MLE). This project is at an early stage of development, and no alpha code is yet available.
JEXP is a small Java framework for the evaluation of expressions parsed from text strings. The code generated by JEXP executes very fast and has a small memory footprint.
The OptControlCentre (OCC) is an user-friendly software package for the optimization of dynamic systems in energy and chemical engineering. Optimization methods include SQP methods as well as a stochastic approach using Simulated Annealing.
The MathForge Application Environment provides users a broad range of Java-based math tools (calculation, visualization, presentation and communication via MathML) and allows developers to leverage existing code while extending MathForge.
Rascal, the Advanced Scientific CALculator, is a platform independent modular calculator. Based on modules for integer, doubles, strings, vectors and matrices it can be easily extended with existing C or C++ code.
A completely portable C++ library,
to provide a standard set of classes similar to Java Common API.
It's highly efficient and it follows the Embedded C++ Standard.
It's FREE (LGPL licensed).
The Random Bit Generator Test Suite will take in large blocks of binary data and attempt
to tell the user what is not random about them. Code developers, mathematicians and
statisticans welcome to help.
This is an ocaml binding for LevMar Minimization library.
The library offers minimization from IR^n to IR^d finding the point which minimizes the distance ||f(p)-x0|| where x0 is the solution in the image space.
The binding enables to use ocaml functions
Fast-Fourier-Transform-based number theory code to test Mersenne numbers for primality using the Lucas-Lehmer test and the Crandall-Fagin irrational-base discrete weighted transform (IBDWT) algorithm (Math. Computation 62 (205), pp.305-324, January 1994)