5 papers
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…
Redshift Classification of Optical Gamma-Ray Bursts using Supervised Learning
Milind Sarkar, Maria Giovanna Dainotti, Nikita S. Khatiya +9
Gamma-ray bursts (GRBs) are among the most luminous explosions in the Universe and serve as powerful probes of the early cosmos. However, the rapid fading of their afterglows and t…
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…
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…