A physical field has an infinite number of degrees of freedom since it has a field value at
each location of a continuous space. Therefore, it is impossible to know a field from finite …

Information field theory (IFT), the information theory for fields, is a mathematical framework
for signal reconstruction and non-parametric inverse problems. Artificial intelligence (AI) and …

Imaging is the process of transforming noisy, incomplete data into a space that humans can
interpret. NIFTy is a Bayesian framework for imaging and has already successfully been …

Knowledge on evolving physical fields is of paramount importance in science, technology,
and economics. Dynamical field inference (DFI) addresses the problem of reconstructing a …

Inference of fields defined in space and time from observational data is a core discipline in
many scientific areas. This work approaches the problem in a Bayesian framework. The …

In this paper, we describe the covariance function of a general Laplacian AR (p) model in
the higher dimension. The speed of decay is considered also showing that the exponential …

Our solar system is part of the Milky Way, a spiral galaxy, illustrated in Fig. 1. 1. The shape of
spiral galaxies is dominated by a disk, which typically possesses several spiral arms and …

Diese Dissertation befasst sich mit der Rekonstruktion des Magnetfeldes der Milchstraße
(GMF für Galaktisches Magnetfeld). Eine genaue Beschreibung des Magnetfeldes ist für …