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Packed Ultra-wideband Mapping Array (PUMA): A Radio Telescope for Cosmology and Transients, , , , , , , , , and 16 other author(s). (2019)cite arxiv:1907.12559Comment: 10 pages + references, 3 figures, 3 tables; project white paper submitted to the Astro2020 decadal survey; further details in updated arXiv:1810.09572.Constraining $M_\nu$ with the Bispectrum II: The Total Information Content of the Galaxy Bispectrum, and . (2020)cite arxiv:2012.02200Comment: 24 pages, 4 figures, the Molino catalog is publicly available at https://changhoonhahn.github.io/molino/.Emulating cosmological multifields with generative adversarial networks, , and . (2022)cite arxiv:2211.05000Comment: 6 pages, 3 figures, Accepted at the Workshop on Machine Learning and the Physical Sciences, Neural Information Processing Systems (NeurIPS) 2022.Fast and realistic large-scale structure from machine-learning-augmented random field simulations., , and . CoRR, (2022)HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks., , , , , , , and . CoRR, (2019)deep21: a Deep Learning Method for 21cm Foreground Removal., , , , , , and . CoRR, (2020)Finding universal relations in subhalo properties with artificial intelligence, , , , , , , , , and . (2021)cite arxiv:2109.04484Comment: 23 pages, 15 figures.The Quijote simulations, , , , , , , , , and 17 other author(s). (2019)cite arxiv:1909.05273Comment: 19 pages, 15 figures. Simulations publicly available at https://github.com/franciscovillaescusa/Quijote-simulations.Learning neutrino effects in Cosmology with Convolutional Neural Networks., , , , , and . CoRR, (2019)Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects., , , , , , , , , and 4 other author(s). CoRR, (2023)