Excited to be organizing a two-day workshop in Edinburgh on Recent advancements in uncertainty quantification for scientific machine learning, artificial intelligence and sampling algorithms.

The workshop brings together experts from seemingly disparate scientific domains such as applied probability, multi-scale modeling, interacting particle systems, optimal transport in Data Science, statistical deep learning, numerical simulation of Stochastic Differential Equations, and uncertainty quantification.

Below is the program:

3/9 Tuesday (1PM-6PM)
1PM-2PM: Aretha Teckentrup, Uncertainty-aware surrogate models for inverse problems
2PM-3PM: Eric Hall, Global Sensitivity Analysis for Deep Learning of Complex Systems
3PM-3:30PM: Coffee break
3:30PM-6PM: Poster session

4/9 Wednesday (10AM-12:30PM)
10AM-11AM: Nicos Georgiou, Various models for queuing systems in tandem 11AM-11:30AM: coffee break
11:30AM-12:30PM: Nikolas Nusken, Bridging transport and variational inference: a new objective for optimal control.