1 code implementation • 15 Aug 2019 • Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Réfrégier
Our results show that the proposed model produces samples of high visual quality, although the statistical analysis reveals that capturing rare features in the data poses significant problems for the generative models.
no code implementations • 27 Jan 2018 • Andres C. Rodriguez, Tomasz Kacprzak, Aurelien Lucchi, Adam Amara, Raphael Sgier, Janis Fluri, Thomas Hofmann, Alexandre Réfrégier
Computational models of the underlying physical processes, such as classical N-body simulations, are extremely resource intensive, as they track the action of gravity in an expanding universe using billions of particles as tracers of the cosmic matter distribution.
no code implementations • 24 Jul 2017 • Tomasz Kacprzak, Jörg Herbel, Adam Amara, Alexandre Réfrégier
This model is trained on a small number of simulations and estimates which regions of the prior space are likely to be accepted into the posterior.
no code implementations • 17 Jul 2017 • Jorit Schmelzle, Aurelien Lucchi, Tomasz Kacprzak, Adam Amara, Raphael Sgier, Alexandre Réfrégier, Thomas Hofmann
We find that our implementation of DCNN outperforms the skewness and kurtosis statistics, especially for high noise levels.