most citedTransfer Learning for Transient Classification: From Simulations to Real Data and ZTF to LSST

6 citations · 6 across the 6 of their papers we have counts for

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astro-ph.IM2026

Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility

Ved G. Shah, Nabeel Rehemtulla, Adam A. Miller +13

Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions for follow-up observations a…

astro-ph.IM2026

SELDON: Supernova Explosions Learned by Deep ODE Networks

Jiezhong Wu, Jack O'Brien, Jennifer Li +6

The discovery rate of optical transients will explode to 10 million public alerts per night once the Vera C. Rubin Observatory's Legacy Survey of Space and Time comes online, overw…

astro-ph.IM2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…

astro-ph.IM2025

Pre-training vision models for the classification of alerts from wide-field time-domain surveys

Nabeel Rehemtulla, Adam A. Miller, Mike Walmsley +15

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Ma…

astro-ph.IM2025★ 6 cited

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…