Public release of codes used for the 5 models explored in [ https://doi.org/10.1016/j.jheap.2026.100684 ]
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Updated
Jul 16, 2026 - Python
Public release of codes used for the 5 models explored in [ https://doi.org/10.1016/j.jheap.2026.100684 ]
Public release of codes for the seven models explored in (https://doi.org/10.1016/j.jheap.2025.100519) [https://arxiv.org/abs/2506.23681] .
GRB-research-archive: A public repository for curated gamma-ray burst datasets and associated supernova metadata. Designed for scalability and reproducibility.
Machine-learning and deep-learning models for reconstructing Gamma-Ray Burst (GRB) light curves during my NAOJ Winter Research Internship (2024–25). Includes LSTM, Bi-LSTM, GRU, Transformer experiments, and classical statistical modeling pipelines.
Key Features: Synthetic Data Generation - Creates realistic GRB-like light curves with power-law decay and noise Interactive Parameters - Adjust data points, noise level, and training epochs via sidebar
Cosmic intelligence research lab — gravitational physics simulations, black hole lensing visualisation, spacetime curvature modelling, and AI-assisted astronomical data analysis and classification tools.
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