26 citations · 45 across the 8 of their papers we have counts for
10 papers
Bayesian Image Reconstruction with Spatially Variant PSFs in X-ray Astronomy
Vincent Eberle, Matteo Guardiani, Margret Westerkamp +4
X-ray observatories introduce unwanted instrumental effects into photon count data that must be accurately accounted for. In particular, the spatially variant point spread function…
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-…
Nonparametric Variational Inference Reconstruction of the Cosmic Expansion History from SNe Ia -- the charm2 code
Iason Saganas, Matteo Guardiani, Natalia Porqueres +1
Cosmological analyses using the latest set of type Ia SNe data weakly favor an evolving dark energy (EDE) model without strongly disfavoring the standard LCDM paradigm. Nonparametr…
The Universal Bayesian Imaging Kit
Torsten Enßlin, Vincent Eberle, Matteo Guardiani +1
Bayesian imaging of astrophysical measurement data shares universal properties across the electromagnetic spectrum: it requires probabilistic descriptions of possible images and sp…
Latent-space Field Tension for Astrophysical Component Detection An application to X-ray imaging
Matteo Guardiani, Vincent Eberle, Margret Westerkamp +3
Modern observatories are designed to deliver increasingly detailed views of astrophysical signals. To fully realize the potential of these observations, principled data-analysis me…
Bayesian Multi-wavelength Imaging of the LMC SN1987A with SRG/eROSITA
Vincent Eberle, Matteo Guardiani, Margret Westerkamp +4
The eROSITA Early Data Release (EDR) and eROSITA All-Sky Survey (eRASS1) data have already revealed a remarkable number of undiscovered X-ray sources. Using Bayesian inference and…
J-UBIK: The JAX-accelerated Universal Bayesian Imaging Kit
Vincent Eberle, Matteo Guardiani, Margret Westerkamp +4
Many advances in astronomy and astrophysics originate from accurate images of the sky emission across multiple wavelengths. This often requires reconstructing spatially and spectra…
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…
First spatio-spectral Bayesian imaging of SN1006 in X-ray
Margret Westerkamp, Vincent Eberle, Matteo Guardiani +6
Supernovae are an important source of energy in the interstellar medium. Young remnants of supernovae have a peak emission in the X-ray region, making them interesting objects for…
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…