Bayesian inference for inverse problems hinges critically on the choice of priors. In the
absence of specific prior information, population-level distributions can serve as effective …

Diffusion generative models have excelled at diverse image generation and reconstruction
tasks across fields. A less explored avenue is their application to discriminative tasks …

Diffusion models have been used in cosmological applications as a generative model for
fast simulations and to reconstruct underlying cosmological fields or astrophysical images …

Reconstructing cosmological initial conditions (ICs) from late-time observations is a difficult
task, which relies on the use of computationally expensive simulators alongside …

Next-generation galaxy surveys promise unprecedented precision in testing gravity at
cosmological scales. However, realising this potential requires accurately modelling the non …

Cosmological hydrodynamical simulations, while the current state-of-the art methodology for
generating theoretical predictions for the large scale structures of the Universe, are among …

Toward a deep learning approach for fast galaxy generation Page 1 ML4ASTRO2 7/11/24
Toward a deep learning approach for fast galaxy generation Tanner Sether PhD Student Advisor …