Related papers: Alert Classification for the ALeRCE Broker System:…

Fink is a broker designed to enable science with large time-domain alert streams such as the one from the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). It exhibits traditional astronomy broker features such as…

The Zwicky Transient Facility (ZTF) survey generates real-time alerts for optical transients, variables, and moving objects discovered in its wide-field survey. We describe the ZTF alert stream distribution and processing (filtering)…

We present a novel pipeline that uses a convolutional neural network (CNN) to improve the detection capability of near-Earth asteroids (NEAs) in the context of planetary defense. Our work aims to minimize the dependency on human…

We describe the fast transient classification algorithm in the center of the kilonova (KN) science module currently implemented in the Fink broker and report classification results based on simulated catalogs and real data from the ZTF…

The ongoing optical time-domain astronomy surveys are routinely reporting fifty transient candidates per night. Here, I investigate the demographics of astronomical transients and supernova classifications reported to the Transient Name…

The labeling cost of large number of bounding boxes is one of the main challenges for training modern object detectors. To reduce the dependence on expensive bounding box annotations, we propose a new semi-supervised object detection…

Modern wide-field time-domain surveys produce alert streams whose scientific potential is often concentrated in rare and unusual events. Efficient discovery therefore requires automated pipelines to be combined with rapid expert validation…

The forthcoming launch of the Ultraviolet Transient Astronomy Satellite (ULTRASAT) will transform our understanding of the transient ultraviolet sky by increasing our ability to identify transients due to its unprecedented 204 deg2 field of…

Event-driven sensors such as LiDAR and dynamic vision sensor (DVS) have found increased attention in high-resolution and high-speed applications. A lot of work has been conducted to enhance recognition accuracy. However, the essential topic…

We evaluate machine learning methods for event classification in the Active-Target Time Projection Chamber detector at the National Superconducting Cyclotron Laboratory (NSCL) at Michigan State University. An automated method to single out…

The advent of large astronomical surveys has made available large and complex data sets. However, the process of discovery and interpretation of each potentially new astronomical source is, many times, still handcrafted. In this context,…

Current synoptic sky surveys monitor large areas of the sky to find variable and transient astronomical sources. As the number of detections per night at a single telescope easily exceeds several thousand, current detection pipelines make…

We present DeepStreaks, a convolutional-neural-network, deep-learning system designed to efficiently identify streaking fast-moving near-Earth objects that are detected in the data of the Zwicky Transient Facility (ZTF), a wide-field,…

Robotic wide-field time-domain surveys, such as the Zwicky Transient Facility and the Asteroid Terrestrial-impact Last Alert System, capture dozens of transients each night. The workflows for discovering and classifying transients in survey…

Current gravitational microlensing surveys are observing hundreds of millions of stars in the Galactic bulge - which makes finding rare microlensing events a challenging tasks. In almost all previous works, microlensing events have been…

We report on the serendipitous observations of Solar System objects imaged during the High cadence Transient Survey (HiTS) 2014 observation campaign. Data from this high cadence, wide field survey was originally analyzed for finding…

The classification of supernovae (SNe) and its impact on our understanding of the explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming…

We have searched for ultra-long (> 100 s) gamma-ray transients in the data from the anticoincidence shield (ACS) of the SPI gamma-ray spectrometer onboard the INTEGRAL orbital observatory and classified them by machine learning methods. We…

Fermi Gamma-ray Space Telescope has detected a diverse range of gamma-ray transients since its launch in 2008. Over the years, Fermi has accumulated an extensive public archive of transient events. Traditional classification methods for…

The recent increase in volume and complexity of available astronomical data has led to a wide use of supervised machine learning techniques. Active learning strategies have been proposed as an alternative to optimize the distribution of…