Scientific Machine Learning and Uncertainty Quantification with Applications

The workshop will be a forum for discussing recent advances in uncertainty quantification, artificial intelligence, and scientific machine learning, with the objective of forging new collaborations and open new avenues of investigation. The workshop topics will range across the following fields:

• Scientific Machine Learning
• Uncertainty Quantification
• Reduced Order Models and Surrogates
• Randomised Numerical Algorithms
• Data-Driven Modelling and Simulation

Note that due to financial and administrative restrictions this workshop is by invitation only.