22 citations · 23 across the 5 of their papers we have counts for
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astro-ph.CO2024
Predicting large scale cosmological structure evolution with generative adversarial network-based autoencoders
Marion Ullmo, Nabila Aghanim, Aurélien Decelle +1
Predicting the nonlinear evolution of cosmic structure from initial conditions is typically approached using Lagrangian, particle-based methods. These techniques excel in terms of…
astro-ph.CO2020★ 22 cited
Encoding large scale cosmological structure with Generative Adversarial Networks
Marion Ullmo, Aurélien Decelle, Nabila Aghanim
Recently a type of neural networks called Generative Adversarial Networks (GANs) has been proposed as a solution for fast generation of simulation-like datasets, in an attempt to b…