SciML Scientific Machine Learning Software Org

@SciML_Org

Open source software for scientific machine learning (#sciml) in #julialang #python #rstats.

sciml.ai

Joined June 2020

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SciML Scientific Machine Learning Software Org
@SciML_Org
May 24, 2021
We are happy to announce a major advance in DifferentialEquations.jl. With improvements to #juilalang BDF methods, the QNDF method outperforms CVODE on the full SciMLBenchmarks suite and has replaced it in recommendations and defaults. Read more: sciml.ai/news/2021/05/2…
SciML Scientific Machine Learning Software Org
@SciML_Org
Jul 6, 2023
Shapley values, a method of explainable Machine Learning (ML), are now in GlobalSensitivity.jl #julialang #sciml. Shapley Effects provide a robust methodology for quantifying the influence of input variables on model outputs. Shapley on Neural ODEs: lnkd.in/gCqRczvB.
SciML Scientific Machine Learning Software Org
@SciML_Org
Oct 8, 2022
Overhauled error messages make it easy to understand incorrect inputs. Major expansions to docstrings, consistent use of style guides, and new #julialang packages for neural operators (DeepONets, Fourier Neural Operators)? See the #sciml ecosystem update!
SciML
From sciml.ai
SciML Scientific Machine Learning Software Org
@SciML_Org
Aug 22, 2022
Are you interested in @SciMLCon 2023? Well we are too, and we're interested in finding out what would make it even better than last year! Please take this survey to share your thoughts: form.jotform.com/222333194908053
SciML Scientific Machine Learning Software Org
@SciML_Org
Aug 17, 2022
New paper by Vaibhav Dixit and Chris Rackauckas on a #julialang #sciml library for Global Sensitivity Analysis (GSA)!
JOSS
@JOSS_TheOJ
Aug 17, 2022
Just published in JOSS: 'GlobalSensitivity.jl: Performant and Parallel Global Sensitivity Analysis with Julia' doi.org/10.21105/joss.…