Search Results for "c kernel"
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Showing 14 open source projects for "c kernel"
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
...We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
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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
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Netgen Mesh Generator
NETGEN is an automatic 3d tetrahedral mesh generator
NETGEN is an automatic 3d tetrahedral mesh generator. It accepts input from constructive solid geometry (CSG) or boundary representation (BRep) from STL file format. The connection to a geometry kernel allows the handling of IGES and STEP files. NETGEN contains modules for mesh optimization and hierarchical mesh refinement. Netgen is open source based on the LGPL license. It is available for Unix/Linux and Windows. -
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libirt
The new site is at http://psychometricon.net/libirt/
The new site is at http://psychometricon.net/libirt/ Library of functions to estimate the items and abilities from the responses of subjects to a questionnaire. The IRT models supported are the logistic model, the multivariate logistic model, the graded model and smoothing by penalization and kernel. -
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Nuklei is a C++ library that implements kernel functions and kernel density estimation for SE(3) data. Nuklei also provides tools for manipulating SE(3) transformations, and for manipulating point clouds.
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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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Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
...Libagf also includes clustering algorithms as well as comparison and validation routines. It is written in C++. -
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ViennaMath
A symbolic math kernel in C++
ViennaMath provides a symbolic math kernel which can be used either for compile-time processing, or for run-time evaluation. Unlike other symbolic math implementations, ViennaMath aims at providing a fast math layer for use with numerical methods such as the finite element method (cf. ViennaFEM) -
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ViennaFEM
A finite element solver using state-of-the-art programming techniques.
ViennaFEM is a library-centric implementation of the finite element method in C++. It features a symbolic math kernel, which manipulates the strong or weak form of the problem and automatically derives the discrete form. ViennaFEM is built on top of the following libraries: ViennaMath provides the symbolic math kernel, ViennaGrid (with ViennaData) allows for a generic grid handling and quantity storage, while ViennaCL provides the linear solvers and GPU acceleration. -
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Lightweight modelling program in which you can create, try and adjust your control (not only) system. Kernel of this program is MBricks - cross-platform collection of bricks. Created in Math Bricks system can be implemented in one *.h file.
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A library for fast computation of Gauss transforms in multiple dimensions, using the Improved Fast Gauss Transform and Approximate Nearest Neighbor searching. This library is useful for efficient Kernel Density Estimation (KDE) using a Gaussian kernel.
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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.
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The Optimized Sparse Kernel Interface (OSKI) Library provides automatically tuned sparse matrix kernels, for use by solver libraries and applications. OSKI is part of the BeBOP project on performance tuning and analysis at U.C. Berkeley. (Go Bears!)
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RSA-IP is a Linux kernel net _protocol_ which encrypts IPv[4;6] using RSA public/private key.Think of it as a kernel level implementation of ssl. RSA needs prime number so we release a prime searcher.
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