Introduction to Uncertainty Quantification in ML

In this half-day online course, you will learn methods to measure and handle uncertainty in machine learning. These approaches play a crucial role in natural science research, helping to make results more reliable and meaningful. By applying UQ methods, you can strengthen both current and future experimental work and increase the impact of your findings.

The course is designed for participants who know Python, have basic statistical knowledge, and are familiar with training models in PyTorch. It will introduce you to the core tools you need to start working with UQ methods. While some theoretical background will be covered, the main focus will be on practical exercises and interactive group discussions.