# SciML/SciMLSensitivity.jl

<https://repo.masters-masters.com/en/repos/SciML/SciMLSensitivity.jl>

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SciML/SciMLSensitivity.jl has 399 stars on GitHub. Its RepoMasters card: Alpha tier. A component of the DiffEq ecosystem for enabling sensitivity analysis for…

| Field | Value |
| --- | --- |
| Owner | [SciML](https://repo.masters-masters.com/en/owners/SciML) |
| Stars | 399 |
| Forks | 93 |
| Language | [Julia](https://repo.masters-masters.com/en/languages/julia) |
| License | None |
| Created | 2016 |
| Topics | differentialequations, sensitivity-analysis, neural-ode, adjoint, backpropogation, neural-sde, ode, sde, dae, dde |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [SciML/SciMLSensitivity.jl](https://github.com/SciML/SciMLSensitivity.jl) |

## Repository

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.

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.