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astro-ph.IM2025
Simulation-Based Pretraining and Domain Adaptation for Astronomical Time Series with Minimal Labeled Data
Rithwik Gupta, Daniel Muthukrishna, Jeroen Audenaert
Astronomical time-series analysis faces a critical limitation: the scarcity of labeled observational data. We present a pre-training approach that leverages simulations, significan…
astro-ph.IM2025
Transfer Learning for Transient Classification: From Simulations to Real Data and ZTF to LSST
Rithwik Gupta, Daniel Muthukrishna, Nabeel Rehemtulla +1
Machine learning has become essential for automated classification of astronomical transients, but current approaches face significant limitations: classifiers trained on simulatio…
astro-ph.IM2024
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical Transients
Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner
Automating real-time anomaly detection is essential for identifying rare transients, with modern survey telescopes generating tens of thousands of alerts per night, and future tele…