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Euclid preparation - LXVIII. Extracting physical parameters from galaxies with machine learning2025 arXiv (Cornell University) preprint Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access
I. Kovačić, M. Baes, Angelos Nersesian, Nick Andreadis, L. Nemani, Laura Bisigello, +78 more
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Euclid preparation. Calibrated intrinsic galaxy alignments in the Euclid Flagship simulation2026 arXiv (Cornell University) preprint Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access
Euclid Collaboration, Romain Paviot, B. Joachimi, N. Tessore, Pau Tallada-Crespí, Nora Elisa Chisari, +92 more
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The FLAMINGO simulation view of cluster progenitors observed in the epoch of reionization with JWST2024 arXiv (Cornell University) preprint Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access
Seunghwan Lim, Sandro Tacchella, Joop Schaye, Matthieu Schaller, Jakob M. Helton, Roi Kugel, +1 more
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Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data2022 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz G. Pitsch
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Euclid preparation. CosmoPostProcess: A simulation calibrated framework for weak lensing selection bias in richness-selected galaxy clusters2026 arXiv (Cornell University) preprint Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access
Euclid Collaboration, R. Ingrao, M. Costanzi, T. Castro, A. Saro, S. Borgani, +94 more
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Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications2026 arXiv (Cornell University) preprint Computer Science Adversarial Robustness in Machine Learning Open access
P. Bechtle, Lucie Flek, A. Jung, Akbar Karimi, Timo Saala, Alexander Schmidt, +4 more
0citations