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GitHub / SciML / SciMLSensitivity.jl
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SciML%2FSciMLSensitivity.jl
Stars: 306
Forks: 66
Open Issues: 101
License: other
Language: Julia
Repo Size: 74.2 MB
Dependencies:
0
Created: over 7 years ago
Updated: about 1 month ago
Last pushed: about 1 month ago
Last synced: about 1 month ago
Commit Stats
Commits: 2374
Authors: 63
Mean commits per author: 37.68
Development Distribution Score: 0.525
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/SciML/SciMLSensitivity.jl
Topics: adjoint, backpropogation, dae, dde, differential-equations, differentialequations, hacktoberfest, neural-ode, neural-sde, ode, scientific-machine-learning, sciml, sde, sensitivity-analysis
Funding links: https://github.com/sponsors/SciML
Files
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