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

Inverse and uncertainty quantification (UQ) problems arise from a large variety of applications, such as earth science, astrophysics, material and plasma science, imaging in geophysics and medicine, nondestructive testing, density estimation, remote sensing, Gaussian process (GP) regression, optimal experimental design, data assimilation and data mining.

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.