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09/05/2022
The SZ flux-mass (Y-M) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback
Ionized gas in the halo circumgalactic medium leaves an imprint on the c...
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06/09/2022
Field Level Neural Network Emulator for Cosmological N-body Simulations
We build a field level emulator for cosmic structure formation that is a...
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06/09/2022
Simple lessons from complex learning: what a neural network model learns about cosmic structure formation
We train a neural network model to predict the full phase space evolutio...
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02/28/2022
Predicting the Thermal Sunyaev-Zel'dovich Field using Modular and Equivariant Set-Based Neural Networks
Theoretical uncertainty limits our ability to extract cosmological infor...
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01/04/2022
Augmenting astrophysical scaling relations with machine learning : application to reducing the SZ flux-mass scatter
Complex systems (stars, supernovae, galaxies, and clusters) often exhibi...
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01/04/2022
The CAMELS project: public data release
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS...
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11/29/2021
Weighing the Milky Way and Andromeda with Artificial Intelligence
We present new constraints on the masses of the halos hosting the Milky ...
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11/16/2021
Inferring halo masses with Graph Neural Networks
Understanding the halo-galaxy connection is fundamental in order to impr...
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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...
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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...
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09/20/2021
Multifield Cosmology with Artificial Intelligence
Astrophysical processes such as feedback from supernovae and active gala...
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01/11/2021
A Bayesian neural network predicts the dissolution of compact planetary systems
Despite over three hundred years of effort, no solutions exist for predi...
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10/29/2020
deep21: a Deep Learning Method for 21cm Foreground Removal
We seek to remove foreground contaminants from 21cm intensity mapping ob...
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08/21/2019
