5 citations · 7 across the 2 of their papers we have counts for
5 papers
Probing evolution of Long GRB properties through their cosmic formation history aided by Machine Learning predicted redshifts
Dhruv S. Bal, Aditya Narendra, Maria Giovanna Dainotti +3
Gamma-ray Bursts (GRBs) are valuable probes of cosmic star formation reaching back into the epoch of reionization, and a large dataset with known redshifts () is an important in…
Probing Evolution of Long Gamma-Ray Burst Properties through Their Cosmic Formation History
Nikita S. Khatiya, Maria Giovanna Dainotti, Aditya Narendra +3
The astrophysics of Long GRB (LGRB) progenitors as well as possible cosmological evolution in their properties still poses many open questions. Previous studies suggest that the LG…
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…
The Machine Learning to reconstruct GRB lightcurves
Maria Giovanna Dainotti, Biagio De Simone, Aditya Narendra +1
The current knowledge in cosmology deals with open problems whose solutions are still under investigation. The main issue is the so-called Hubble constant () tension, namely,…