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Multi-label (ML) data deals with multiple classes associated with individual samples at the same time. This leads to the co-occurrence of several classes repeatedly, which indicates some existing correlation among them. In this article, the…

Machine Learning · Computer Science 2021-09-23 Anwesha Law , Ashish Ghosh

We present the catalog of X-ray sources detected in a shallow Chandra survey of the inner 2 by 0.8 degrees of the Galaxy, and in two deeper observations of the Radio Arches and Sgr B2. The catalog contains 1352 objects that are…

Astrophysics · Physics 2009-11-11 M. P. Muno , F. E. Bauer , R. M. Bandyopadhyay , Q. D. Wang

XMM and Chandra opened a new area for the study of clusters of galaxies. Not only for cluster physics but also, for the detection of faint and distant clusters that were inaccessible with previous missions. This article presents 66…

Large area catalogs of galaxy clusters constructed from ROSAT All Sky Survey provide the base for our knowledge on the population of clusters thanks to the long-term multiwavelength efforts on their follow-up. Advent of large area…

Transfer learning is a common practice that alleviates the need for extensive data to train neural networks. It is performed by pre-training a model using a source dataset and fine-tuning it for a target task. However, not every source…

Machine Learning · Computer Science 2024-10-01 Jiseok Lee , Brian Kenji Iwana

Procedures based on current methods to detect sources in X-ray images are applied to simulated XMM images. All significant instrumental effects are taken into account, and two kinds of sources are considered -- unresolved sources…

Astrophysics · Physics 2009-11-06 I. Valtchanov , M. Pierre , R. Gastaud

[ABRIDGED] The XMM Cluster Survey (XCS) is predicted to detect thousands of clusters observed serendipitously in XMM-Newton pointings. We investigate automating optical follow-up of cluster candidates using the SDSS public archive,…

We present a systematic search for periodic X-ray sources in the bulge of M31, using ~ 2 Ms of archival Chandra observations spanning a temporal baseline of 16 years. Utilizing the Gregory-Loredo algorithm that is designed for…

High Energy Astrophysical Phenomena · Physics 2024-04-29 Jiachang Zhang , Tong Bao , Zhiyuan Li

Machine Learning (ML) is increasingly used to automate impactful decisions, which leads to concerns regarding their correctness, reliability, and fairness. We envision highly-automated software platforms to assist data scientists with…

Databases · Computer Science 2024-09-04 Stefan Grafberger

We introduce the New-ANGELS program, an XMM-Newton survey of $\sim7.2\rm~deg^2$ area around M 31, which aims to study the X-ray populations in M 31 disk and the X-ray emitting hot gas in the inner halo of M 31 up to 30 kpc. In this first…

High Energy Astrophysical Phenomena · Physics 2023-06-21 Rui Huang , Jiang-Tao Li , Wei Cui , Joel N. Bregman , Xiang-Dong Li , Gabriele Ponti , Zhijie Qu , Q. Daniel Wang , Yi Zhang

We have detected 523 sources in a survey of the Small Magellanic Cloud (SMC) Wing with Chandra. By cross-correlating the X-ray data with optical and near-infrared catalogues we have found 300 matches. Using a technique that combines X-ray…

We carry out classification of 4330 X-ray sources in the 2XMMi-DR3 catalog. They are selected under the requirement of being a point source with multiple XMM-Newton observations and at least one detection with the signal-to-noise ratio…

High Energy Astrophysical Phenomena · Physics 2015-06-05 Dacheng Lin , Natalie A. Webb , Didier Barret

We present the final release of the multi-wavelength XMM-LSS data set,covering the full survey area of 11.1 square degrees, with X-ray data processed with the latest XMM-LSS pipeline version. The present publication supersedes the Pierre et…

Cosmology and Nongalactic Astrophysics · Physics 2012-11-20 L. Chiappetti , N. Clerc , F. Pacaud , M. Pierre , A. Gueguen , L. Paioro , M. Polletta , O. Melnyk , A. Elyiv , J. Surdej , L. Faccioli

We report on our search for distant clusters of galaxies based on optical and X-ray follow up observations of X-ray candidates from the SHARC survey. Based on the assumption that the absence of bright optical or radio counterparts to…

Astrophysics · Physics 2009-11-13 C. Adami , M. P. Ulmer , F. Durret , G. Covone , E. Cypriano

With the advance of technology, entities can be observed in multiple views. Multiple views containing different types of features can be used for clustering. Although multi-view clustering has been successfully applied in many applications,…

Machine Learning · Computer Science 2016-04-20 Weixiang Shao , Jiawei Zhang , Lifang He , Philip S. Yu

In software development, the identification of source code file experts is an important task. Identifying these experts helps to improve software maintenance and evolution activities, such as developing new features, code reviews, and bug…

Software Engineering · Computer Science 2022-08-17 Otávio Cury , Guilherme Avelino , Pedro Santos Neto , Ricardo Britto , Marco Túlio Valente

The unprecedented volume and quality of data from space- and ground-based telescopes present an opportunity for machine learning to identify new classes of variable stars and peculiar systems that may have been overlooked by traditional…

Solar and Stellar Astrophysics · Physics 2026-01-14 P. Ranaivomanana , C. Johnston , G. Iorio , P. J. Groot , M. Uzundag , T. Kupfer , C. Aerts

Since its launch in 1999, the XMM-\textit{Newton} mission has compiled the largest catalogue of serendipitous X-ray sources, with the 3XMM being the third version of this catalogue. This is because of the combination of a large effective…

Astrophysics of Galaxies · Physics 2022-02-02 A. Ruiz , I. Georgantopoulos , A. Corral

We describe the X-ray analysis procedure of the on-going Chandra Multiwavelength Plane (ChaMPlane) survey and report the initial results from the analysis of 15 selected anti-Galactic center observations (90 deg < l < 270 deg). We describe…

Large language models (LLMs) often generate fluent but factually incorrect outputs, known as hallucinations, which undermine their reliability in real-world applications. While uncertainty estimation has emerged as a promising strategy for…

Machine Learning · Computer Science 2025-05-13 Pei-Fu Guo , Yun-Da Tsai , Shou-De Lin
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