Hyrax is a GPU-enabled open-source framework for the full ML lifecycle in astronomy, with demonstrations of unsupervised discovery and classification on real survey data from Rubin, ZTF, and other projects.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3representative citing papers
Early LSST data recovers known ultracool dwarfs and yields 89 candidates with 17 unique to this work, forecasting over 17,000 detections in Data Preview 2 using synthetic populations.
Analysis of ~600 RR Lyrae in DP1 shows PWZ-based distances match literature (mean offset 0.01 mag) while PLZ distances are systematically larger and amplitudes mismatch evolved models, due to limited light-curve sampling.
citing papers explorer
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Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid
Hyrax is a GPU-enabled open-source framework for the full ML lifecycle in astronomy, with demonstrations of unsupervised discovery and classification on real survey data from Rubin, ZTF, and other projects.
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Searching for Ultracool Dwarfs in Early LSST Data Products
Early LSST data recovers known ultracool dwarfs and yields 89 candidates with 17 unique to this work, forecasting over 17,000 detections in Data Preview 2 using synthetic populations.
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Exploring RR Lyrae Variable Stars in the Vera C. Rubin Observatory Data Preview 1
Analysis of ~600 RR Lyrae in DP1 shows PWZ-based distances match literature (mean offset 0.01 mag) while PLZ distances are systematically larger and amplitudes mismatch evolved models, due to limited light-curve sampling.