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.
- Getting Started with UncertainSCI
- Developer Documentation
- API Documentation
Jake Bergquist, Dana Brooks, Zexin Liu, Rob MacLeod, Akil Narayan, Sumientra Rampersad, Lindsay Rupp, Jess Tate, Dan White
This project was supported by grants from the National Institute of Biomedical Imaging and Bioengineering (U24EB029012) from the National Institutes of Health.