SciML/DiffEqFlux.jl

DiffEqFlux.jl

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Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

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Julia · MIT · Last push 2026-10-18

Official repository & installation ↗
neural-odeneural-sdeneural-pdeneural-ddeneural-differential-equationsstiff-odeordinary-differential-equationsstochastic-differential-equationsdelay-differential-equationspartial-differential-equations

GitValue · Value evidence

Unscored · Evidence coverage 0%

Provisional rubric; documentation and runtime testing are separate. Missing evidence does not imply low value.

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Get the project

git clone https://github.com/SciML/DiffEqFlux.jl.git

Cloning downloads the source. For dependencies and installation, follow the project README.

Related projects & alternative candidates

Related domains do not imply feature parity. Review official documentation and licenses.