24 citations · 38 across the 8 of their papers we have counts for
5 papers · 1 filter
Gamma-Ray Burst Light Curve Reconstruction: A Comparative Machine and Deep Learning Analysis
A. Manchanda, A. Kaushal, M. G. Dainotti +14
Gamma-Ray Bursts (GRBs), observed at high-z, are probes of the evolution of the Universe and can be used as cosmological tools. Thus, we need correlations with small dispersion amo…
GRB Redshift Estimation using Machine Learning and the Associated Web-App
Aditya Narendra, Maria Dainotti, Milind Sarkar +7
Context. Gamma-ray bursts (GRBs), observed at redshifts as high as 9.4, could serve as valuable probes for investigating the distant Universe. However, this necessitates an increas…
GRB Redshift Classifier to Follow-up High-Redshift GRBs Using Supervised Machine Learning
Maria Giovanna Dainotti, Shubham Bhardwaj, Christopher Cook +8
Gamma-ray bursts (GRBs) are intense, short-lived bursts of gamma-ray radiation observed up to a high redshift () due to their luminosities. Thus, they can serve as cosmo…
Gamma-ray Bursts as Distance Indicators by a Statistical Learning Approach
Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo +6
Gamma-ray bursts (GRBs) can be probes of the early universe, but currently, only 26% of GRBs observed by the Neil Gehrels Swift Observatory GRBs have known redshifts () due to o…
Inferring the redshift of more than 150 GRBs with a Machine Learning Ensemble model
Maria Giovanna Dainotti, Elias Taira, Eric Wang +8
Gamma-Ray Bursts (GRBs), due to their high luminosities are detected up to redshift 10, and thus have the potential to be vital cosmological probes of early processes in the univer…