Non-Gaussian information from weak lensing data via deep learning
Gupta, Arushi, Matilla, José Manuel Zorrilla, Hsu, Daniel, Haiman, Zoltán·2018·Physical Review D
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- Cosmological inference with cosmic shearPeter L. Taylor · 2019 · UCL Discovery (University College London)
- Extracting cosmological information from small scales in weak gravitational lensing dataJosé Manuel Zorrilla Matilla · 2020
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- Deep learning generated observations of galaxy clusters from dark-matter-only simulationsAndrés Caro, D. de Andres, W. Cui, G. Yepes, M. De Petris, A. Ferragamo, Félicien Schiltz, Am'elie Nef · 2024 · RAS Techniques and Instruments
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- Non-Gaussian cosmology : theoretical and statistical challenges for modern galaxy surveysMatteo Rizzato · 2019
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- Field-level weak lensing cosmology with 60 simulations using multifidelity simulation-based inferenceAlex A Saoulis, Kiyam Lin, N Jeffrey, Maximilian von Wietersheim-Kramsta, Davide Piras, A. Spurio Mancini, Ana M. G. Ferreira, Benjamin Joachimi · 2026 · Monthly Notices of the Royal Astronomical Society
- Probing cosmology through higher-order CMB lensing statisticsShu-Fan Chen, J. Colin Hill, Zoltán Haiman · 2026 · Physical review. D/Physical review. D.
- Replicating weak-lensing summary-statistic covariances with normalizing flowsAnonymous, Leander Thiele, Jia Liu · 2026 · Physical review. D/Physical review. D.
- First Application of Weak Lensing Peak Steepness Statistics to HSC Year 1 Data: Effectively Probing Halo Density ProfilesZiwei Li, Xiangkun Liu, Tianyu Zhang, An Zhao, Chuzhong Pan, Yuan Shuo, Qiao Wang, Zuhui Fan · 2026 · The Astrophysical Journal
- DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications (AICosmo'19 workshop)Michaël Defferrard · 2019 · Figshare