research
∙
04/04/2023
The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites
We present CAMELS-ASTRID, the third suite of hydrodynamical simulations ...
share
research
∙
03/24/2023
Physics-informed neural networks in the recreation of hydrodynamic simulations from dark matter
Physics-informed neural networks have emerged as a coherent framework fo...
research
∙
01/04/2022
The CAMELS project: public data release
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS...
research
∙
11/16/2021
Inferring halo masses with Graph Neural Networks
Understanding the halo-galaxy connection is fundamental in order to impr...
research
∙
09/22/2021
The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence
We present the Cosmology and Astrophysics with MachinE Learning Simulati...
research
∙
09/21/2021
Robust marginalization of baryonic effects for cosmological inference at the field level
We train neural networks to perform likelihood-free inference from (25 h...
research
∙
09/20/2021
Multifield Cosmology with Artificial Intelligence
Astrophysical processes such as feedback from supernovae and active gala...
research
∙
12/10/2020
