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juliahub.com : SciMLSensitivity : 7.49.0
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.
Registry -
Documentation -
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purl: pkg:julia/[email protected]
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Related tag:
v7.49.0
Dependencies
- ADTypes 0.1-0.2
- Adapt 1-3
- ArrayInterface 7
- ChainRulesCore 0.10.7-0.10,1
- DiffEqBase 6.93.0-6
- DiffEqCallbacks 2.29.0-2
- DiffEqNoiseProcess 4.1.4-5
- Distributions 0.24-0.25
- EllipsisNotation 1
- Enzyme 0.11.6-0.11
- FiniteDiff 2
- ForwardDiff 0.10
- FunctionProperties 0.1
- FunctionWrappersWrappers 0.1
- Functors 0.4
- GPUArraysCore 0.1
- LinearAlgebra 0.0.0,1
- LinearSolve 2
- Markdown 0.0.0,1
- OrdinaryDiffEq 6.19.1-6
- Parameters 0.12
- PreallocationTools 0.4.4-0.4
- QuadGK 2.1.0-2
- Random 0.0.0,1
- RandomNumbers 1.5.3-1
- RecursiveArrayTools 2.4.2-3
- Reexport 0.2,1
- ReverseDiff 1.9.0-1
- SciMLBase 1.66.0-2
- SciMLOperators 0.1-0.3
- SparseDiffTools 2.5.0-2
- StaticArrays 1.8.0-1
- StaticArraysCore 1.4.0-1
- Statistics 1
- StochasticDiffEq 6.20.0-6
- Tracker 0.2
- TruncatedStacktraces 1.2.0-1
- Zygote 0.6
- julia 1.9.0-1