Uncertainty quantification

Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known. An example would be to predict the acceleration of a human body in a head-on crash with another car: even if the speed was exactly known, small differences in the manufacturing of individual cars, how tightly every bolt has been tightened, etc., will lead to different results that can only be predicted in a statistical sense.

Uncertainty quantification - Wikipedia Jump to content From Wikipedia, the free encyclopedia Science of characterizing uncertainties Uncertainty quantification ( UQ ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known. An example would be to predict the acceleration of a human body in a head-on crash with another car: even if the speed was exactly known, small differences in the manufacturing of individual cars

related reading

• uncertain-modern-topics-in-uncertainty-estimation.pdfcalibration-tutorial.github.io
• Ale Epistat.berkeley.edu
• Fox_Ulkumen.pdfstat.berkeley.edu
• SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimatesarxiv.org
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• Gregory Gundersengregorygundersen.com
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• How to Measure Anything — LessWronglesswrong.com
• Bracketing Inference with Uncertainty Quantification: A Reliability Pipeline for Neural Aerodynamic Surrogatesresearchsquare.com
• Writing - betanalpha.github.iobetanalpha.github.io