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DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains., , , , , , , , and . CoRR, (2021)The Evolution of Star Formation Activity in Cluster Galaxies Over $0.15<z<1.5$, , , , , and . (2016)cite arxiv:1610.01498Comment: 18 pages, 11 figures. Accepted for publication in The Astrophysical Journal.Introducing the Illustris Project: Simulating the coevolution of dark and visible matter in the Universe, , , , , , , , and . (2014)cite arxiv:1405.2921Comment: 33 pages, 26 figures, 3 tables. Submitted to MNRAS. The official Illustris website can be found at http://www.illustris-project.org.A Census of the Bright z=8.5-11 Universe with the Hubble and Spitzer Space Telescopes in the CANDELS Fields, , , , , , , , , and 14 other author(s). (2021)cite arxiv:2106.13813Comment: 47 figures, 25 pages, 10 tables, submitted to the Astrophysical Journal.The illustris simulation: Public data release., , , , , , , , , and 5 other author(s). Astron. Comput., (2015)DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification., , , , , , , , and . Mach. Learn. Sci. Technol., 3 (3): 35007 (2022)DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification., , , , , , , , and . CoRR, (2021)Galaxy Morphology and Star Formation in the Illustris Simulation at z=0, , , , , , , , , and 2 other author(s). (2015)cite arxiv:1502.07747Comment: 23 pages, 13 figures, submitted to MNRAS.DeepMerge: Classifying High-redshift Merging Galaxies with Deep Neural Networks., , , and . CoRR, (2020)Robustness of deep learning algorithms in astronomy - galaxy morphology studies., , , , , , , , and . CoRR, (2021)