An universal equation to predict Omega_m from halo and galaxy catalogues
Helen Shao presents her work discovering a new an universal equation that can predict the value of Omega_m from halo and galaxy catalogues
Robust field-level likelihood-free inference with galaxy catalogues
Natali de Santi presents her work on robust field-level likelihood-free inference with galaxy catalogues
Machine Learning to improve scaling relations for cluster cosmology
Jay Wadekar presents his work on improving scaling relations for cluster cosmology with machine learning. Papers (https://arxiv.org/abs/2201.01305 & https://arxiv.org/abs/2209.02075).
Robust field-level inference with dark matter halos
Helen Shao presents the results of her paper (2209.06843) on robust field-level inference with dark matter halos
Sultan Hassan presents HIFlow in Cosmology Talks
Lucia Perez presents CAMELS-SAM in cosmology talks.
Weighing the Milky Way and Andromeda with AI
Pablo Villanueva-Domingo presents his papers (2111.08683, 2111.14874) in cosmology talks
Percent-level constraints on baryonic feedback with spectral distortion measurements
Leander Thiele presents his paper (2201.01663) in cosmology talks
Breaking baryon-cosmology degeneracy with the electron density power spectrum
Andrina Nicola presents her paper (2201.04142) in cosmology talks.
Augmenting astrophysical scaling relations with machine learning
Jay Wadekar presents his paper (2201.01305) in cosmology talks
Cosmology with one galaxy?
Francisco Villaescusa-Navarro presents his paper (2201.02202) in cosmology talks
CAMELS data release
Francisco Villaescusa-Navarro talks about the CAMELS data release
Finding universal relations in subhalo properties with artificial intelligence
Helen Shao & Francisco Villaescusa-Navarro describe their paper 2109.04484 in cosmology talks
The CAMELS project
Daniel Angles-Alcazar, Francisco Villaescusa-Navarro, and Shy Genel talk about CAMELS in cosmology from home