Main topics of the workshop are the application and development of Bayesian inference, AI/ML-approaches and the maximum entropy principle to inverse problems in science, machine learning, information theory and engineering.

Inverse and uncertainty quantification problems arise from a large variety of applications, such as astrophysics, earth science, material and plasma science, imaging in geophysics and medicine, nondestructive testing, density estimation, remote sensing, Gaussian process regression, active learning, causal inference, data assimilation and data mining.

There will be two special topic sessions:
time domain, multi-wavelengths and multi-messenger astrophysics
understanding artificial intelligence

The workshop thus invites contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference and AI/ML.