Work

UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation Pipelines

Year: 2023

Type: software-paper

Abstract: Tate et al., (2023). UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation Pipelines. Journal of Open Source Software, 8(90), 4249, https://doi.org/10.21105/joss.04249

Source: The Journal of Open Source Software

DOI: 10.21105/joss.04249

Authors: Jess Tate, Zexin Liu, Jake A Bergquist, Sumientra Rampersad, Dan White, Chantel Charlebois, Lindsay Rupp, Dana H Brooks, Rob S MacLeod, Akil Narayan

Institutions: University of Utah, Northeastern University, University of Massachusetts Boston

Language: English

Topic: Probabilistic and Robust Engineering Design

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

Funders: National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering

Award: Integration of Uncertainty Quantification with SCIRun Bioelectric Field Simulation Pipeline

OpenAlex ID: W4388192173

Cites: 14

Cited by: 5

Related to: 10