26 citations · 52 across the 12 of their papers we have counts for
12 papers
Milky Way Atlas: A radial-velocity-resolved, three-dimensional map of H I within 1.25 kpc
Lewis McCallum, Laurin Söding, Mareike Berkner +9
We present a velocity-resolved three-dimensional map of local atomic hydrogen (HI) within 1.25 kpc of the Sun, tackling the challenge of converting emission from position-position-…
Application of Bayesian Statistical Tools to SKA Telescopes Polarization Surveys to Study Magnetization of the Large-scale Structure of the Universe
Valentina Vacca, Sebastian Hutschenreuter, Andrea Cabriolu +18
Understanding cosmological magnetic fields requires a detailed knowledge of magnetism in the different environments of the large-scale structure of the Universe. Magnetic fields ar…
A Three-Dimensional Tomographic Reconstruction of the Galactic Cosmic-Ray Proton Density
Hanieh Zandinejad, Jakob Roth, Vo Hong Minh Phan +7
Cosmic rays (CRs) are a ubiquitous non-thermal component of the interstellar medium (ISM). A data-driven three-dimensional (3D) map of their distribution is essential for understan…
DEFROST: Detecting Excess in Faraday Rotation thrOugh Sophisticated analysis Techniques
Valentina Vacca, Sebastian Hutschenreuter, Andrea Cabriolu +7
Understanding origin and evolution of cosmological magnetic fields requires knowledge of magnetic fields in different extragalactic environments. In this context, a powerful tool i…
Towards a Field Based Bayesian Evidence Inference from Nested Sampling Data
Margret Westerkamp, Jakob Roth, Philipp Frank +2
Nested sampling (NS) is a stochastic method for computing the log-evidence of a Bayesian problem. It relies on stochastic estimates of prior volumes enclosed by likelihood contours…
fast-resolve: Fast Bayesian Radio Interferometric Imaging
Jakob Roth, Philipp Frank, Hertzog L. Bester +3
Context: Interferometric imaging is algorithmically and computationally challenging as there is no unique inversion from the measurement data back to the sky maps, and the datasets…
JAXbind: Bind any function to JAX
Jakob Roth, Martin Reinecke, Gordian Edenhofer
JAX is widely used in machine learning and scientific computing, the latter of which often relies on existing high-performance code that we would ideally like to incorporate into J…
Re-Envisioning Numerical Information Field Theory (NIFTy.re): A Library for Gaussian Processes and Variational Inference
Gordian Edenhofer, Philipp Frank, Jakob Roth +7
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 ap…
Inferring Evidence from Nested Sampling Data via Information Field Theory
Margret Westerkamp, Jakob Roth, Philipp Frank +2
Nested sampling provides an estimate of the evidence of a Bayesian inference problem via probing the likelihood as a function of the enclosed prior volume. However, the lack of pre…
A BRAIN study to tackle image analysis with artificial intelligence in the ALMA 2030 era
Fabrizia Guglielmetti, Michele Delli Veneri, Ivano Baronchelli +9
An ESO internal ALMA development study, BRAIN, is addressing the ill-posed inverse problem of synthesis image analysis employing astrostatistics and astroinformatics. These emergin…
Fast-Cadence High-Contrast Imaging with Information Field Theory
Jakob Roth, Gianluca Li Causi, Vincenzo Testa +2
Although many exoplanets have been indirectly detected over the last years, direct imaging of them with ground-based telescopes remains challenging. In the presence of atmospheric…
Causal, Bayesian, & Non-parametric Modeling of the SARS-CoV-2 Viral Load Distribution vs. Patient's Age
Matteo Guardiani, Philipp Frank, Andrija Kostić +4
The viral load of patients infected with SARS-CoV-2 varies on logarithmic scales and possibly with age. Controversial claims have been made in the literature regarding whether the…