2 papers
astro-ph.CO2025
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.HE2024
Nonparametric signal separation in very-high-energy gamma ray observations with probabilistic neural networks
Marion Ullmo, Emmanuel Moulin
An intriguing challenge in observational astronomy is the separation signals in areas where multiple signals intersect. A typical instance of this in very-high-energy (VHE, E$\gtrs…