26 citations · 29 across the 6 of their papers we have counts for
5 papers · 1 filter
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…