activity
20172022
most citedCosmological model discrimination with Deep Learning

24 citations · 44 across the 4 of their papers we have counts for

collaborators

16 papers

astro-ph.CO20224 cited

Cosmology from Galaxy Redshift Surveys with PointNet

Sotiris Anagnostidis, Arne Thomsen, Tomasz Kacprzak +4

In recent years, deep learning approaches have achieved state-of-the-art results in the analysis of point cloud data. In cosmology, galaxy redshift surveys resemble such a permutat…

astro-ph.CO20221 cited

DeepLSS: breaking parameter degeneracies in large scale structure with deep learning analysis of combined probes

Tomasz Kacprzak, Janis Fluri

In classical cosmological analysis of large scale structure surveys with 2-pt functions, the parameter measurement precision is limited by several key degeneracies within the cosmo…

astro-ph.CO2020

Cosmological Forecast for non-Gaussian Statistics in large-scale weak Lensing Surveys

Dominik Zürcher, Janis Fluri, Raphael Sgier +2

Cosmic shear data contains a large amount of cosmological information encapsulated in the non-Gaussian features of the weak lensing mass maps. This information can be extracted usi…

astro-ph.CO2020

Predicting Cosmological Observables with PyCosmo

F. Tarsitano, U. Schmitt, A. Refregier +7

Current and upcoming cosmological experiments open a new era of precision cosmology, thus demanding accurate theoretical predictions for cosmological observables. Because of the co…

astro-ph.GA2020

Measurement of the B-band Galaxy Luminosity Function with Approximate Bayesian Computation

Luca Tortorelli, Martina Fagioli, Jörg Herbel +3

The galaxy Luminosity Function (LF) is a key observable for galaxy formation, evolution studies and for cosmology. In this work, we propose a novel technique to forward model wide-…

astro-ph.CO2019

Baryonic effects for weak lensing. Part II. Combination with X-ray data and extended cosmologies

Aurel Schneider, Alexandre Refregier, Sebastian Grandis +6

An accurate modelling of baryonic feedback effects is required to exploit the full potential of future weak-lensing surveys such as Euclid or LSST. In this second paper in a series…