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Statistics in uncertainty quantification and uncertainty quantification in statistics, by Dr. Amy Braverman.

Monday, February 26, 2024 - 09:15 to 10:15
Aula Magna Paolo Budinich
Aula Magna

Traditionally the UQ community has focused on quantifying uncertainties in the predictions made by deterministic models. Statistics provides an alternative formalism for modeling unknown processes using data. These two approaches represent the ends of a spectrum of knowledge about the processes of interest, and therefore one or the other may be more appropriate depending on the problem. However, we are not restricted to just one or the other - hybrid approaches are possible, and indeed are used for some problems. In addition, statistical tools are already heavily used in UQ, and various applied mathematical tools are already incorporated into statistical computing. The point is that the endeavor known as “uncertainty quantification” is much broader than the way it is traditionally understood, and it should be reframed to acknowledge that reality. Not only will this increase synergies among existing techniques and lead to more powerful approaches to a wider range of problems, but the increased diversity of viewpoints will benefit the intellectual environment of our community. This presentation will discuss these issues in the hopes of stimulating a conversation about how we can move in this direction.

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