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We explore the possibility of using deep learning to generate multifield images from state-of-the-art hydrodynamic simulations of the CAMELS project.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Fast cosmic web simulations with generative adversarial networks
Andres C Rodriguez, Tomasz Kacprzak, Aurelien Lucchi, et al · 2018
Earlier work this paper cites.
Pylians: Python libraries for the analysis of numerical simulations
Francisco Villaescusa-Navarro · 2018
Earlier work this paper cites.
Cosmogan: creating high-fidelity weak lensing convergence maps using generative adversarial networks
Mustafa Mustafa, Deborah Bard, Wahid Bhimji, et al · 2019
Earlier work this paper cites.
Higan: Cosmic neutral hydrogen with generative adversarial networks
Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro, et al · 2019
Earlier work this paper cites.
Cosmological n-body simulations: a challenge for scalable generative models
Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, et al · 2019
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Cosmological simulations of galaxy formation
Mark Vogelsberger, Federico Marinacci, Paul Torrey, and Ewald Puchwein · 2020
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Nonlinear 3d cosmic web simulation with heavy-tailed generative adversarial networks
Richard M Feder, Philippe Berger, and George Stein · 2020
Cited alongside, same era.
Towards faster and stabilized gan training for high-fidelity few-shot image synthesis
Bingchen Liu, Yizhe Zhu, Kunpeng Song, and Ahmed Elgammal · 2020
Cited alongside, same era.
Emulation of cosmological mass maps with conditional generative adversarial networks
Nathanaël Perraudin, Sandro Marcon, Aurelien Lucchi, and Tomasz Kacprzak · 2021
Cited alongside, same era.
Investigating cosmological gan emulators using latent space interpolation
Andrius Tamosiunas, Hans A Winther, Kazuya Koyama, et al · 2021
Later among the works it cites.
The camels project: Cosmology and astrophysics with machine-learning simulations
Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, et al · 2021
Later among the works it cites.
Cosmic voids in gan-generated maps of large-scale structure
Olivia Curtis, Tereasa G Brainerd, and Anthony Hernandez · 2022
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The camels multifield data set: Learning the universe’s fundamental parameters with artificial intelligence
Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar, et al · 2022
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The camels project: public data release
Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, et al · 2022
Closest in time.
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