Scientific videos

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

HIFlow

Sultan Hassan presents HIFlow in Cosmology Talks

CAMELS-SAM

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