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https://github.com/avik-pal/scimlsensitivity.jl

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.

https://github.com/avik-pal/scimlsensitivity.jl

Science Score: 18.0%

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    CITATION.cff file
    Found CITATION.cff file
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    .zenodo.json file
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    Low similarity (9.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

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A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.

Basic Info
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 19
  • Releases: 0
Fork of SciML/SciMLSensitivity.jl
Created over 4 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

SciMLSensitivity.jl

Join the chat at https://julialang.zulipchat.com #sciml-bridged Global Docs

codecov Build Status Build status

ColPrac: Contributor's Guide on Collaborative Practices for Community Packages SciML Code Style

SciMLSensitivity.jl is a component package in the SciML Scientific Machine Learning ecosystem. It holds the sensitivity analysis utilities. Users interested in using this functionality should check out DifferentialEquations.jl.

Tutorials and Documentation

For information on using the package, see the stable documentation. Use the in-development documentation for the version of the documentation, which contains the unreleased features.

Owner

  • Name: Avik Pal
  • Login: avik-pal
  • Kind: user
  • Location: Cambridge, MA
  • Company: Massachusetts Institute of Technology

PhD Student @mit || Prev: BTech CSE IITK

Citation (CITATION.bib) 

@article{rackauckas2020universal,
  title={Universal differential equations for scientific machine learning},
  author={Rackauckas, Christopher and Ma, Yingbo and Martensen, Julius and Warner, Collin and Zubov, Kirill and Supekar, Rohit and Skinner, Dominic and Ramadhan, Ali},
  journal={arXiv preprint arXiv:2001.04385},
  year={2020}
}

@article{DifferentialEquations.jl-2017,
 author = {Rackauckas, Christopher and Nie, Qing},
 doi = {10.5334/jors.151},
 journal = {The Journal of Open Research Software},
 keywords = {Applied Mathematics},
 note = {Exported from https://app.dimensions.ai on 2019/05/05},
 number = {1},
 pages = {},
 title = {DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia},
 url = {https://app.dimensions.ai/details/publication/pub.1085583166 and http://openresearchsoftware.metajnl.com/articles/10.5334/jors.151/galley/245/download/},
 volume = {5},
 year = {2017}
}

GitHub Events

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