| Fast cosmic web simulations with generative adversarial networks AC Rodriguez, T Kacprzak, A Lucchi, A Amara, R Sgier, J Fluri, ... Computational Astrophysics and Cosmology 5 (1), 1-11, 2018 | 143 | 2018 |
| Cosmological constraints with deep learning from KiDS-450 weak lensing maps J Fluri, T Kacprzak, A Lucchi, A Refregier, A Amara, T Hofmann, ... Physical Review D 100 (6), 063514, 2019 | 122 | 2019 |
| Cosmological constraints from noisy convergence maps through deep learning J Fluri, T Kacprzak, A Refregier, A Amara, A Lucchi, T Hofmann Physical Review D 98 (12), 123518, 2018 | 80 | 2018 |
| Cosmological Forecast for non-Gaussian Statistics in large-scale weak Lensing Surveys D Zürcher, J Fluri, R Sgier, T Kacprzak, A Refregier Journal of Cosmology and Astroparticle Physics 2021 (01), 028, 2021 | 56 | 2021 |
| Dark energy survey year 3 results: Cosmology with peaks using an emulator approach D Zürcher, J Fluri, R Sgier, T Kacprzak, M Gatti, C Doux, L Whiteway, ... Monthly Notices of the Royal Astronomical Society 511 (2), 2075-2104, 2022 | 50 | 2022 |
| Full analysis of KiDS-1000 weak lensing maps using deep learning J Fluri, T Kacprzak, A Lucchi, A Schneider, A Refregier, T Hofmann Physical Review D 105 (8), 083518, 2022 | 33 | 2022 |
| Weak lensing peak statistics in the era of large scale cosmological surveys J Fluri, T Kacprzak, R Sgier, A Refregier, A Amara Journal of Cosmology and Astroparticle Physics 2018 (10), 051, 2018 | 30 | 2018 |
| CosmoGridV1: a simulated 𝗐CDM theory prediction for map-level cosmological inference T Kacprzak, J Fluri, A Schneider, A Refregier, J Stadel Journal of Cosmology and Astroparticle Physics 2023 (02), 050, 2023 | 18 | 2023 |
| Deeplss: Breaking parameter degeneracies in large-scale structure with deep-learning analysis of combined probes T Kacprzak, J Fluri Physical Review X 12 (3), 031029, 2022 | 15 | 2022 |
| Cosmological parameter estimation and inference using deep summaries J Fluri, T Kacprzak, A Refregier, A Lucchi, T Hofmann Physical Review D 104 (12), 123526, 2021 | 14 | 2021 |
| Fast lightcones for combined cosmological probes R Sgier, J Fluri, J Herbel, A Réfrégier, A Amara, T Kacprzak, A Nicola Journal of Cosmology and Astroparticle Physics 2021 (02), 047, 2021 | 13 | 2021 |
| Predicting cosmological observables with PyCosmo F Tarsitano, U Schmitt, A Refregier, J Fluri, R Sgier, A Nicola, J Herbel, ... Astronomy and Computing 36, 100484, 2021 | 12 | 2021 |
| Towards a full wCDM map-based analysis for weak lensing surveys D Zürcher, J Fluri, V Ajani, S Fischbacher, A Refregier, T Kacprzak Monthly Notices of the Royal Astronomical Society 525 (1), 761-784, 2023 | 10 | 2023 |
| Combined 13× 2-point analysis of the Cosmic Microwave Background and Large-Scale Structure: implications for the S8-tension and neutrino mass constraints R Sgier, C Lorenz, A Refregier, J Fluri, D Zürcher, F Tarsitano arXiv preprint arXiv:2110.03815, 2021 | 10 | 2021 |
| A tomographic spherical mass map emulator of the KiDS-1000 survey using conditional generative adversarial networks TWH Yiu, J Fluri, T Kacprzak Journal of Cosmology and Astroparticle Physics 2022 (12), 013, 2022 | 5 | 2022 |
| Symbolic implementation of extensions of the PyCosmo Boltzmann solver B Moser, CS Lorenz, U Schmitt, A Refregier, J Fluri, R Sgier, F Tarsitano, ... Astronomy and Computing 40, 100603, 2022 | 5 | 2022 |
| Assessing theoretical uncertainties for cosmological constraints from weak lensing surveys T Tan, D Zürcher, J Fluri, A Refregier, F Tarsitano, T Kacprzak Monthly Notices of the Royal Astronomical Society 522 (3), 3766-3783, 2023 | 2 | 2023 |
| Cosmological Parameter Inference with Deep Learning J Fluri ETH Zurich, 2022 | | 2022 |
| A tomographic spherical mass map emulator of the KiDS-1000 survey using conditional generative adversarial networks T Wing Hei Yiu, J Fluri, T Kacprzak arXiv e-prints, arXiv: 2112.12741, 2021 | | 2021 |
| Combined -point analysis of the Cosmic Microwave Background and Large-Scale Structure: implications for the -tension and neutrino mass constraints R Sgier, C Lorenz, A Refregier, J Fluri, D Zürcher, F Tarsitano arXiv preprint arXiv:2110.03815, 2021 | | 2021 |
