K Cranmer, J Brehmer… - Proceedings of the …, 2020 - National Acad Sciences
Many domains of science have developed complex simulations to describe phenomena of interest. While these simulations provide high-fidelity models, they are poorly suited for …
The dawn of the twenty-first century came with very positive prospects for gravity, cosmology, and astrophysics. Technological progress made it possible for cosmology to enter to its …
The CAMELS Project: Cosmology and Astrophysics with Machine-learning Simulations - IOPscience This site uses cookies. By continuing to use this site you agree to our use of cookies …
The Quijote Simulations - IOPscience This site uses cookies. By continuing to use this site you agree to our use of cookies. To find out more, see our Privacy and Cookies policy. Close this …
Cosmic inflation provides a window to the highest energy densities accessible in nature, far beyond those achievable in any realistic terrestrial experiment. Theoretical insights into the …
CH Hahn, M Eickenberg, S Ho, J Hou… - Proceedings of the …, 2023 - National Acad Sciences
We present cosmological constraints from a simulation-based inference (SBI) analysis of galaxy clustering from the SimBIG forward modeling framework. SimBIG leverages the …
In many cosmological inference problems, the likelihood (the probability of the observed data as a function of the unknown parameters) is unknown or intractable. This necessitates …
C Durkan, I Murray… - … conference on machine …, 2020 - proceedings.mlr.press
Likelihood-free methods perform parameter inference in stochastic simulator models where evaluating the likelihood is intractable but sampling synthetic data is possible. One class of …
While astrophysical and cosmological probes provide a remarkably precise and consistent picture of the quantity and general properties of dark matter, its fundamental nature remains …