Related papers: VaST: a variability search toolkit

The Variables and Slow Transients Survey (VAST) on the Australian Square Kilometre Array Pathfinder (ASKAP) is designed to detect highly variable and transient radio sources on timescales from 5 seconds to $\sim 5$ years. In this paper, we…

In this contribution we present the FAST, which is a comprehensive software suite that aims to streamline and automatically manage the forecast of atmospheric and astroclimatic parameters (provided respectively by Meso-Nh and Astro-Meso-Nh…

We present the selection algorithm and anticipated results for the Time Domain Spectroscopic Survey (TDSS). TDSS is an SDSS-IV eBOSS subproject that will provide initial identification spectra of approximately 220,000 luminosity-variable…

We explored the AllWISE catalogue of the Wide-field Infrared Survey Explorer mission and identified Young Stellar Object candidates. Reliable 2MASS and WISE photometric data combined with Planck dust opacity values were used to build our…

The fast classification of new variable stars is an important step in making them available for further research. Selection of science targets from large databases is much more efficient if they have been classified first. Defining the…

Variable Star Network (VSNET, http://www.kusastro.kyoto-u.ac.jp/vsnet/) is a global professional-amateur network of researchers in variable stars and related objects, particularly in transient objects, such as cataclysmic variables, black…

Vista Variables in the Via Lactea (VVV) is an ESO Public Survey that is performing a variability survey of the Galactic bulge and part of the inner disk using ESO's Visible and Infrared Survey Telescope for Astronomy (VISTA). The survey…

We introduce the public version of the BAyesian STellar Algorithm (BASTA), an open-source code written in {\tt Python} to determine stellar properties based on a set of astrophysical observables. BASTA has been specifically designed to…

An overview is given of the Permanent All Sky Survey (PASS) project. The primary goal of PASS is the detection of all transiting giant planets in the entire sky, complete for stellar systems of magnitudes ~ 5.5-10.5. Since the sample stars…

Text-to-image retrieval is an essential task in cross-modal information retrieval, i.e., retrieving relevant images from a large and unlabelled dataset given textual queries. In this paper, we propose VisualSparta, a novel (Visual-text…

The AMIDST Toolbox is a software for scalable probabilistic machine learning with a spe- cial focus on (massive) streaming data. The toolbox supports a flexible modeling language based on probabilistic graphical models with latent variables…

The MAterials Simulation Toolkit (MAST) is a workflow manager and post-processing tool for ab initio defect and diffusion workflows. MAST codifies research knowledge and best practices for such workflows, and allows for the generation and…

With a combination of adaptive optics imaging and a multi-epoch common proper motion search, we have conducted a large volume-limited (D $\le$ 75 pc) multiplicity survey of A-type stars, sensitive to companions beyond 30 au. The sample for…

We analyzed data accumulated during 2005 and 2006 by the Taiwan-American Occultation Survey (TAOS) in order to detect short-period variable stars (periods of <~ 1 hour) such as delta Scuti. TAOS is designed for the detection of stellar…

The reliability of detecting source variability in sparsely and irregularly sampled X-ray light curves is investigated. This is motivated by the unprecedented survey capabilities of eROSITA onboard SRG, providing light curves for many…

While previous CNN-based models have exhibited promising results for salient object detection (SOD), their ability to explore global long-range dependencies is restricted. Our previous work, the Visual Saliency Transformer (VST), addressed…

In long baseline interferometry, the raw fringe contrast must be calibrated to obtain the true visibility and then those observables that can be interpreted in terms of astrophysical parameters. The selection of suitable calibration stars…

Weakly supervised video anomaly detection (WS-VAD) is to distinguish anomalies from normal events based on discriminative representations. Most existing works are limited in insufficient video representations. In this work, we develop a…

Object Detection is the task of identifying the existence of an object class instance and locating it within an image. Difficulties in handling high intra-class variations constitute major obstacles to achieving high performance on standard…

We aim to construct an exceptionally deep (V ~< 27) catalog of variable objects in selected Galactic and extragalactic fields visited multiple times by the Hubble Space Telescope (HST). While HST observations of some of these fields were…