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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript
A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.
(Experimental, a lot of bugs) Automatic fingering generator for piano scores, determining optimal fingering using Model-Based Reinforcement Learning, written in the Julia language.