23 – 29 May 2022

University of Dundee, Scotland, UK

This focused research workshop in the area of Probability and Statistics will consider significant new developments in uncertainty quantification for scientific machine learning (UQ for SciML) and its impact on simulation-aided decision support in the emerging area of Simulation Intelligence. The aim of the workshop is to examine the mathematics underpinning UQ for SciML that take into account uncertainty of the underlying parameters and physics-based models.

Organiser:

Eric Hall (Dundee)

Participants:

Eric Hall (Dundee)
Abdul-Lateef Haji-Ali (Heriot-Watt)
Jonathan Spence (Heriot-Watt)
Markos Katsoulakis (Massachusetts Amherst)
Panagiota Birmpa (Massachusetts Amherst)