arXiv Machine Learning
Automatic classification pipeline for glitches in the Virgo detector
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Flexible Gravitational-Wave Parameter Estimation with Transformers
arXiv:2512. 02968v2 Announce Type: replace-cross Abstract: Gravitational-wave data analysis relies on accurate and efficient methods to extract physical information from noisy detector signals, yet the increasing rate and complexity of observations represent a growing challenge.
arXiv Machine Learning
Jul 2
Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility
arXiv:2607. 00228v1 Announce Type: cross Abstract: 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 central challenge in time-domain astronomy.
arXiv Machine Learning
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Identifying Gems from Roman RAPIDly
arXiv:2606. 05103v1 Announce Type: new Abstract: The Nancy Grace Roman Space Telescope (Roman), set for launch as early as September 2026, will conduct wide-field infrared imaging surveys with unprecedented spatial resolution and cadence, enabling the discovery of millions of astronomical transients.
arXiv Machine Learning
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MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data
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arXiv AI
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STARLINC: Satellite Trail Artifact Removal using Inter-Frame Correlation
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Machine Learning and Deep Learning for Exoplanet Detection and Atmospheric Characterization with JWST and the Upcoming Ariel Mission
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