uncertainty quantification

Abderrahmene Ben Romdhane

M.S. Student, Stochastic Numerics Research Group

numerical analysis Computational finance uncertainty quantification

Arved Bartuska

Postdoctoral Research Fellow, Stochastic Numerics Research Group

numerical analysis uncertainty quantification optimal experimental design

Uncertainty Quantification with Conformal Prediction in Energy Data

Tarek AlSkaif, Associate Professor, Energy Informatics, Wageningen University (WUR)

Feb 1, 12:00 - 13:00

B9 L2 R2325

conformal prediction machine learning uncertainty quantification

The talk will introduce the fundamentals of conformal prediction (CP) - a flexible, model-agnostic uncertainty quantification framework for generating statistically valid uncertainty estimates in energy applications - and demonstrate how it can be layered on top of machine learning models to produce reliable prediction intervals.

Amal Alghamdi

Founder, Impact Alpha, Saudi Arabia

HPC Python data analysis finite element method uncertainty quantification