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Found 3 papers, 1 papers with code
The CAMELS project: public data release
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning.
The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence
We present the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from 2, 000 distinct simulated universes at several cosmic times.
SHAPing the Gas: Understanding Gas Shapes in Dark Matter Haloes with Interpretable Machine Learning
In this study we explore a machine learning approach for modelling the dependence of gas shapes on dark matter and baryonic properties.
Cosmology and Nongalactic Astrophysics
