Context. The characterization of the interior of an exoplanet is an inverse problem. The
solution requires statistical methods such as Bayesian inference. Current methods employ …

Connecting the gas in H ii regions to the underlying source of the ionizing radiation can help
us constrain the physical processes of stellar feedback and how H ii regions evolve over …

Context. Spectroscopic observations of high-redshift galaxies slowly reveal the same
complexity of the interstellar medium (ISM) as expected from resolved observations in …

Stellar feedback, the energetic interaction between young stars and their birthplace, plays
an important role in the star formation history of the Universe and the evolution of the …

Intelligent systems in interventional healthcare depend on the reliable perception of the
environment. In this context, photoacoustic tomography (PAT) has emerged as a non …

Context. New spectroscopic surveys will increase the number of astronomical objects in
need of characterisation by more than an order of magnitude. Machine learning tools are …

Aims. We introduce a new deep-learning approach for the reconstruction of 3D dust density
and temperature distributions from multi-wavelength dust emission observations on the …

Aims. We introduce a new deep-learning tool that estimates stellar parameters (eg effective
temperature, surface gravity, and extinction) of young low-mass stars by coupling the …

Classifying ionised nebulae in nearby galaxies is crucial to studying stellar feedback
mechanisms and understanding the physical conditions of the interstellar medium. This …

We develop a new analysis method that allows us to compare multidimensional observables
to a theoretical model. The method is based on unsupervised clustering algorithms which …