Search Results for "computer science projects"
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Showing 49 open source projects for "computer science projects"
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Armadillo
fast C++ library for linear algebra & scientific computing
* 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:... -
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UoMASM
A C++ Active Shape Model Library from the University of Manchester
A library and associated tools for building and searching with Active Shape Models (ASM). It builds on the VXL computer vision libraries. Includes a GUI tool to search new images with the ASM. Depends on: VXL, Qt (Version 4), UoMqVXL -
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pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* 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... -
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javascript-algorithms
JavaScript implementations of computer science algorithms
javascript-algorithms is a repository that implements a comprehensive collection of classic data structures and algorithmic solutions in JavaScript — including sorting, searching, graph algorithms, dynamic programming, and more. It serves as a learning and reference resource for developers wanting to understand how standard algorithms can be expressed in JavaScript, bridging the gap between theoretical algorithm knowledge and practical implementation usable in web or Node.js contexts.... -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
...The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. ... -
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go-algorithms
Algorithms and data structures for golang
go-algorithms is an open-source educational repository that provides implementations of common algorithms and data structures written in the Go programming language. The project is designed primarily as a learning resource to help developers understand how fundamental computer science concepts can be implemented idiomatically in Go. It includes a wide range of classic sorting, searching, and numerical algorithms alongside basic collection structures such as stacks, queues, linked lists, and binary trees. The repository is organized into clear directories by topic, making it easy for learners to explore specific categories of algorithms. ... -
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Axiom is a computer algebra system. It consists of an interpreter, a compiler and a library of algorithms. Axiom is an excellent research platform as well as a useful tool for scientific programming.
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Data Structures and Algorithms in JS
Data Structures and Algorithms explained and implemented in JavaScript
...However, to make use of them properly, you have to know the tradeoffs so you can choose the best tool for the job. Improve your problem-solving skills and become a stronger developer by understanding fundamental computer science concepts. -
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PMCGPU
Parallel simulators for Membrane Computing on the GPU
...Other parallel platforms are also welcome (multicore and manycore, FPGAs, etc). This project has been initiated by the Research Group on Natural Computing (Department of Computer Science and Artificial Intelligence, University of Seville). PMCGPU was born inside the P-Lingua project, of the same research group. PMCGPU is a GNU project, so all the applications developed within it are released under the GPLv3 license. Just contact us if you want to participate. Please, visit the Wiki of the project for further information. -
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NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
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OpenANN
Basic Artificial Neural Network
OpenANN is a basic artificial neural network toolset. It is not being actively maintained. For performance neural networking, consider an alternative (such as https://sourceforge.net/projects/openann-project or https://www.tensorflow.org) -
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algorithms.js
Classic algorithms and data structures implemented in JavaScript
Traditional Computer Science algorithms and data structures implemented in JavaScript. Algorithms such as collatzConjecture, extendedEuclidean, fastPower, fibonacci, findDivisors, fisherYates, gcd (Greatest common divisor), greatestDifference, lcm (Least common multiple), newtonSqrt, nextPermutation, powerSet, reservoirSampling, shannonEntropy, etc. -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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New Terrain and 3D Map System
a very lightweight advanced terrain-rendering and 3D map rendering sys
A very lightweight advanced terrain-rendering and 3D map rendering system. Minimal dependencies: OpenGL, SDL. It's distrib in 2-3 separate modules: 1. the C++ implementation of the terrain- and/or surface- rendering Algorithms I have developed: both a multithread and a non-multithread variant is relaeased. 2. Seme as at point 1. , but with a road-network rendering and collision-detection module I wrote before. It also adds some trees at the top of the terrain. (multitread vesion not... -
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GeoPDEs
A package for Isogeometric Analysis in Octave and Matlab
GeoPDEs is a suite of software tools for research on Isogeometric Analysis of PDEs. GeoPDEs is free software implemented in Octave and fully compatible with Matlab. GeoPDEs is no longer developed at SF, and has moved to GitHub. Please visit http://rafavzqz.github.io/geopdes/ The mailing list will remain active. Releases up to 2.0.4 can be found here. From version 2.1.0 onward, see https://github.com/rafavzqz/geopdes -
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Bat2015
Bachelor of Science (Informatik)
The toolkit glpk supports methods for mixed integer linear programming (MILP). These methods solve Capital Budgeting Problems (CBP). Unfortunately, glpk does not support any multithreading and there is no feature to distribute problems via network connections. Today, this is a pitiable sight, because modern computer systems are coupled by networks and support multi threading. We create a distributed system with Apache thrift and the C-API of glpk. Now, it is possible to use as many cores in... -
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That project (RMOL) aims at giving developers concerned by the Revenue Management arena a library delivering a reference implementation for most of the published algorithms and methods. That library is intended to be used in simulated environment: it does not intend to be used in real world production systems.
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HeaDDaCHe
Hashed dynamic determinants for convex hulls
...This consists of efficient implementations of dynamic determinant algorithms and a hash table that stores intermediate results (matrices and determinants) in order to be used in subsequent steps of the algorithm. Related papers: V.Fisikopoulos, L.Peñaranda. Faster Geometric Algorithms via Dynamic Determinant Computation. In Algorithms – ESA 2012, Lecture Notes in Computer Science Volume 7501, 2012, pp 443-454. -
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C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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jmathstudio - Java Image/Signal toolkit
Java toolkit for discrete Image and Signal processing.
JMathStudio is a Java based digital image and signal processing toolkit/library. It is simple to use, portable, light (~300 Kb), extendable and free. Full source code available at https://github.com/bhavyaajani/jmathstudio Android compatible JMathStudio is available @ https://sourceforge.net/projects/jmathstudio-android/ -
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PyVision Computer Vision Toolkit
A Python computer vision library
PyVision is a object-oriented Computer Vision Toolkit for researchers that contains vision and machine learning algorithms and algorithm analysis and easily interfaces with scipy/numpy, PIL, opencv and other computer and machine learning libraries. -
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BudgetedSVM
BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification
We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classi fication problems with millions of... -
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Distributed Multithread Apriori (DMTA)
A parallel implementation using MPI and OpenMP to Apriori algorithm
...The algorithm was generated as a result of a project developed by André Camilo Bolina, under the guidance of teachers Marluce Rodrigues Pereira, Ahmed Ali Abdalla Esmin and Denilson Alves Pereira, in Department of Computer Science at Federal University of Lavras. The results of this project were published in the Revista de Sistemas de Informação da FSMA and is available in http://www.fsma.edu.br/si/edicao11/FSMA_SI_2013_1_Principal_1.html -
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ProximityForest
Efficient Approximate Nearest Neighbors for General Metric Spaces
A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer...
