SciML / SciML/DataDrivenDiffEq.jl
Structural Identifiability Analysis of dynamical systems SIAN: Global identifiabilty app
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 430
- Forks
- 58
- Avg merge
- 6h 29m
- Merged PRs (30d)
- 28
Description
@AlCap23 This paper https://cs.nyu.edu/~pogudin/global.pdf is relevant to DataDrivenDiffEq. It comes with the corresponding app https://github.com/pogudingleb/Global_Identifiability/blob/master/GlobalIdentifiability.mpl in Maple that proves to be particularly efficient. @ChrisRackauckas Note Example 2.13 on the Lotka-Volterra ODE system and why some parameters are difficult to identify.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the linked paper, especially Example 2.13 on the Lotka-Volterra system, and inspect GlobalIdentifiability.mpl in the referenced repository. Compare the Maple app's structural identifiability analysis with DataDrivenDiffEq.jl; the issue does not define a concrete implementation scope or completion criterion.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100