Search Results for "kernel virtual machine"

It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of...

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

Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities.

Free binary Turing Machine simulator with a graphical user interface and possibility to save your files. Language : French (no translation available)

FVM2 is VM for running machines like Markov algorithms, Turing machine and so on. FVM2 has debugger with step mode and breakpoints. Goal of this project is to help students with studying Theory of computation. FVM2 shows how complex code works within a real machine. Currently the only implemented machine is Markov algorithms.

...With Java 2, it provides an open-source solution for listening to harmonies so generated by planetary motion. This program can run on any computer provided with a Java Virtual Machine (Rev 1.5 or greater). JAVA 2, system independent. Purpose:to encourage research in harmony in astronomy, math and music. Obstacles:math, DSP/synthesis, networks, astronomy. Features:audio, database, graphics Technologies: Telnet, .WAV audio, oggvorbis, other audio

A Matlab toolbox for interfacing with the pure JAVA numerical library Snifflib. This toolbox provides convenience m-files for interoperability with Snifflib from within an active Matlab session running a JAVA virtual machine.

OSlash is a c++ framework for developing decentralized cloud computing services. It includes a programming environment and virtual machine for assembling networks of processing nodes coordinate their operations through message passing.

Java OpenCL Process Virtual Machine. Spring IoC based framework for complex data analysis with OpenCL computing.

Bidirectional computer, bicomp, is a virtual machine designed to aid in the research of complexity. bicomp runs its programs in forward or reverse. The program either produces a result from two inputs, or a list of possible inputs given a result.

A open source, multiplatform, fractal generator and explorer. Includes Mandelbrot, Julia, Lambda and others popular formulas. Also includes formula reader to create new fractals. It can save PNG images. Requires Java Virtual Machine.

ChemCpp is a C++ toolbox for chemoinformatics focusing on the computation of kernel functions between chemical compounds. Together with Support Vector Machines, these kernel functions find natural applications for virtual screening of molecules.

The Wolfram Machine project is an effort to create a set of documentation and useful modules (both hardware and software) for a computing architecture based on the mathematical theories presented in Steven Wolfram's book _A_New_Kind_of_Science_.

JCalc is GUI calculator written entirely in Java. It can be run cross-platform on any OS with a Java Virtual Machine. It shall be portable, stable, and efficient.

Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other