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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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fPotencia is programmed in C++, but my intention is to bring JAVA, C#, Python and perhaps MATLAB versions of it. All of them in native code and whenever possible with the same modular structure.
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.