19 citations · 24 across the 10 of their papers we have counts for
6 papers · 1 filter
NAPTIME: A Neural-Process Framework for Rubin Alert Classification
Nicholas Earl, Siddharth Chaini, K. Decker French +3
The Vera C. Rubin Observatory Legacy Survey of Space and Time will produce a high-volume stream of irregularly sampled multiband alerts for which spectroscopic confirmation will be…
Toward decision-aware AI for LSST-scale time-domain astronomy
C. R. Bom, A. Mahabal, F. Bianco +27
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will generate approximately (10^7) alerts per night, pushing time-domain astronomy beyond pipelines that trea…
Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP
Siddharth Chaini, Federica B. Bianco, Ashish Mahabal
Astrophysical observations from Earth are subject to weather, environmental, and scientific constraints that lead to sparse, irregular light curves. On the eve of the Vera C. Rubin…
In Search of the Unknown Unknowns: A Multi-Metric Distance Ensemble for Out of Distribution Anomaly Detection in Astronomical Surveys
Siddharth Chaini, Federica B. Bianco, Ashish Mahabal
Distance-based methods involve the computation of distance values between features and are a well-established paradigm in machine learning. In anomaly detection, anomalies are iden…
Light Curve Classification with DistClassiPy: a new distance-based classifier
Siddharth Chaini, Ashish Mahabal, Ajit Kembhavi +1
The rise of synoptic sky surveys has ushered in an era of big data in time-domain astronomy, making data science and machine learning essential tools for studying celestial objects…
Astronomical Classification of Light Curves with an Ensemble of Gated Recurrent Units
Siddharth Chaini, Soumya Sanjay Kumar
With an ever-increasing amount of astronomical data being collected, manual classification has become obsolete; and machine learning is the only way forward. Keeping this in mind,…