https://github.com/avik-pal/steadystatediffeq.jl
Solvers for steady states in scientific machine learning (SciML)
Science Score: 18.0%
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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Low similarity (5.0%) to scientific vocabulary
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Solvers for steady states in scientific machine learning (SciML)
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- Stars: 0
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Fork of SciML/SteadyStateDiffEq.jl
Created almost 5 years ago
· Last pushed over 3 years ago
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Citation
README.md
SteadyStateDiffEq.jl
SteadyStateDiffEq.jl is a component package in the DifferentialEquations ecosystem. It holds the steady state solvers for differential equations. While completely independent and usable on its own, users interested in using this functionality should check out DifferentialEquations.jl.
Owner
- Name: Avik Pal
- Login: avik-pal
- Kind: user
- Location: Cambridge, MA
- Company: Massachusetts Institute of Technology
- Website: https://avik-pal.github.io
- Twitter: avikpal1410
- Repositories: 46
- Profile: https://github.com/avik-pal
PhD Student @mit || Prev: BTech CSE IITK
Citation (CITATION.bib)
@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}
}
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