Armadillo C++ matrix library
Fast C++ library for linear algebra (matrix maths) and scientific computing. Easy to use functions and syntax, deliberately similar to Matlab. Uses template meta-programming techniques.
Also provides efficient wrappers for LAPACK, BLAS, ATLAS, ARPACK and SuperLU libraries, including high-performance versions such as OpenBLAS and Intel MKL.
Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc.
For more details, see http://arma.sourceforge.net
Also provides efficient wrappers for LAPACK, BLAS, ATLAS, ARPACK and SuperLU libraries, including high-performance versions such as OpenBLAS and Intel MKL.
Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc.
For more details, see http://arma.sourceforge.net
Features
- Easy to use - has many MATLAB like functions
- Useful for prototyping directly in C++
- Useful for conversion of research code into production environments
- Permissively licensed - can be used in proprietary software and products
- Used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc
- Efficient classes for vectors, matrices, cubes (1st, 2nd, 3rd order tensors)
- Supports dense and sparse matrices
- Fast singular value decomposition (SVD), eigen decomposition, QR, LU, Cholesky, FFT
- Clustering using k-means and Gaussian Mixture Models (GMM)
- Automatic vectorisation of expressions (SIMD)
- Contiguous and non-contiguous submatrices
- Automatically combines several operations into one to increase speed and efficiency
- Automatically uses OpenMP for speedups
About MRF
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