Model and Parametric Uncertainty
UncertainSCI is a Python-based toolkit that harnesses modern techniques to estimate model and parametric uncertainty.
Please join us on June 25th for the Uncertainty Quantification Workshop
as part of the 11th biennial meeting on Functional Imaging and Modeling of the Heart (FIMH-2021)
as part of the 11th biennial meeting on Functional Imaging and Modeling of the Heart (FIMH-2021)
Overview
Documentation
Support
Acknowledgements
UncertainSCI
UncertainSCI is a Python-based toolkit that harnesses modern techniques to estimate model and parametric uncertainty, with a particular emphasis on needs for biomedical simulations and applications. This toolkit enables non-intrusive integration of these techniques with well-established biomedical simulation software.Introduction to UncertainSCI
Applications
Background Math
Cardiac Bioelectricity
Brain Neuromodulation
Applications
Background Math
Cardiac Bioelectricity
Brain Neuromodulation
Acknowledgements
Please include the following acknowledgement in work using this software:"This work was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under grant number U24EB029012”
