Michelle Ntampaka
0000-0002-0144-387X
9 papers found
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A Hybrid Deep Learning Approach to Cosmological Constraints from Galaxy Redshift Surveys
A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
Using X-Ray Morphological Parameters to Strengthen Galaxy Cluster Mass Estimates via Machine Learning
Cluster Cosmology with the Velocity Distribution Function of the HeCS-SZ Sample
Machine Learning Applied to the Reionization History of the Universe in the 21 cm Signal
A Deep Learning Approach to Galaxy Cluster X-Ray Masses
The Velocity Distribution Function of Galaxy Clusters as a Cosmological Probe
Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning
A Machine Learning Approach for Dynamical Mass Measurements of Galaxy Clusters
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