Related papers: Gamma-ray burst light curve reconstruction with pr…
This thesis comprises the first three chapters dedicated to providing an overview of Gamma Ray-Bursts (GRBs), their properties, the instrumentation used to detect them, and Artificial Intelligence (AI) applications in the context of GRBs,…
Gamma-ray bursts are a complex, non-linear system that evolves very rapidly through stages of vastly different conditions. They evolve from scales of few hundred kilometers where they are very dense and hot to cold and tenuous on scales of…
The angular dependence of emission in gamma-ray bursts (GRB) is of fundamental importance in understanding the underlying physical mechanisms, as well as in multimessenger search efforts. We examine the prospects of using reconstructed GRB…
Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in…
Gamma-ray bursts (GRBs) show diverse X-ray afterglow light-curves, including breaks and plateaus, whose physical origins remain debated. Previous claims linked high-energy ($E \ge 100$ MeV) detection to X-ray afterglow complexity or plateau…
Part I describes the analysis of periodic and transient signals in EGRET data. A method to search for the transient flux from gamma-ray bursts independent of triggers from other gamma-ray instruments is developed. Several known gamma-ray…
Classification of gamma-ray bursts (GRBs) has been a long-standing puzzle in high-energy astrophysics. Recent observations challenge the traditional short vs. long viewpoint, where long GRBs are thought to originate from the collapse of…
Future video prediction is an ill-posed Computer Vision problem that recently received much attention. Its main challenges are the high variability in video content, the propagation of errors through time, and the non-specificity of the…
The empirical classification of gamma-ray bursts (GRBs) into long and short GRBs based on their durations is already firmly established. This empirical classification is generally linked to the physical classification of GRBs originating…
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 universe. Fulfilling this potential requires a large sample of…
Recent advances in computed tomography (CT) imaging, especially with dual-robot systems, have introduced new challenges for scan trajectory optimization. This paper presents a novel approach using Gated Recurrent Units (GRUs) to optimize CT…
We present a powerful new tool for fitting broadband gamma-ray burst afterglow data, which can be used to determine the burst explosion parameters and the synchrotron radiation parameters. By making use of scale invariance between…
Sequence modeling is a critical yet challenging task with wide-ranging applications, especially in time series forecasting for domains like weather prediction, temperature monitoring, and energy load forecasting. Transformers, with their…
This paper proposes a Fast Graph Convolutional Neural Network (FGRNN) architecture to predict sequences with an underlying graph structure. The proposed architecture addresses the limitations of the standard recurrent neural network (RNN),…
Gamma-ray bursts (GRBs) are the most luminous explosions and can be detectable out to the edge of Universe. It has long been thought they can extend the Hubble diagram to very high redshifts. Several correlations between temporal or…
Sorted by the photon fluences of short Gamma-ray Bursts (SGRBs) detected by the Fermi- Gamma Ray Burst Monitor (GBM), nine brightest bursts are selected to perform a comprehensive analysis. All GRB lightcurves are fitted well by 1 to 3…
Context: Gamma Ray Burst models predict the broadband spectral evolution and the temporal evolution of the energy flux. In contrast, standard data analysis tools and data repositories provide count-rate data, or use single flux conversion…
Studies of high-redshift gamma-ray bursts (GRBs) provide important information about the early Universe such as the rates of stellar collapsars and mergers, the metallicity content, constraints on the re-ionization period, and probes of the…
Gamma-ray bursts (GRBs) associated with gravitational wave events are, and will likely continue to be, viewed at a larger inclination than GRBs without gravitational wave detections. As demonstrated by the afterglow of GW170817, this…
The reconstruction of unsteady flow fields from limited measurements is a challenging and crucial task for many engineering applications. Machine learning models are gaining popularity for solving this problem due to their ability to learn…