Ecosyste.ms: Packages
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Top 4.8% dependent packages on juliahub.com
Top 0.4% forks on juliahub.com
juliahub.com : DiffEqFlux
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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purl: pkg:julia/DiffEqFlux
Keywords: scientific-ml, neural-pde, physics-informed-learning, pinn, stochastic-differential-equations, scientific-machine-learning, neural-sdes, neural-jump-diffusions, delay-differential-equations, partial-differential-equations, neural-sde, neural-networks, differentialequations, neural-ode, ordinary-differential-equations, differential-equations, stiff-ode, neural-differential-equations, neural-dde, scientific-ai
License: MIT
Latest release: about 1 month ago
First release: over 5 years ago
Dependent packages: 14
Stars: 835 on GitHub
Forks: 151 on GitHub
Total Commits: 1474
Committers: 93
Average commits per author: 15.849
Development Distribution Score (DDS): 0.626
More commit stats: commits.ecosyste.ms
See more repository details: repos.ecosyste.ms
Funding links: https://github.com/sponsors/SciML
Last synced: 1 day ago