GitHub / SciML / ModelingToolkit.jl

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

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Commits: 4137
Authors: 143
Mean commits per author: 28.93
Development Distribution Score: 0.663
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Topics: acausal, computer-algebra, dae, dde, delay-differential-equations, differential-equations, equation-based, julia, nonlinear-programming, ode, optimization, ordinary-differential-equations, pde, scientific-machine-learning, sciml, sde, stochastic-differential-equations, symbolic, symbolic-computation, symbolic-numerics

Funding links: https://github.com/sponsors/SciML

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