Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Ćiprijanović A."'
Assessing the quality of aleatoric uncertainty estimates from uncertainty quantification (UQ) deep learning methods is important in scientific contexts, where uncertainty is physically meaningful and important to characterize and interpret exactly. W
Externí odkaz:
http://arxiv.org/abs/2411.08587
Modeling strong gravitational lenses is computationally expensive for the complex data from modern and next-generation cosmic surveys. Deep learning has emerged as a promising approach for finding lenses and predicting lensing parameters, such as the
Externí odkaz:
http://arxiv.org/abs/2411.03334
Modeling strong gravitational lenses is prohibitively expensive for modern and next-generation cosmic survey data. Neural posterior estimation (NPE), a simulation-based inference (SBI) approach, has been studied as an avenue for efficient analysis of
Externí odkaz:
http://arxiv.org/abs/2410.16347
In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial ins
Externí odkaz:
http://arxiv.org/abs/2407.17292
Publikováno v:
Serbian Astronomical Journal, Vol 2019, Iss 198, Pp 13-23 (2019)
We present detection of 64 H II regions, three superbubbles and two optical supernova remnant (SNR) candidates in the nearby irregular galaxy NGC 2366. The SNR candidates were detected by applying [S II]/Hα ratio criterion to observations made with
Externí odkaz:
https://doaj.org/article/e8b9c0f4cad54d849e8e6de417e52a2d
Autor:
Roncoli, Andrea, Ćiprijanović, Aleksandra, Voetberg, Maggie, Villaescusa-Navarro, Francisco, Nord, Brian
Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and
Externí odkaz:
http://arxiv.org/abs/2311.01588
Autor:
Savić, Đorđe V., Jankov, Isidora, Yu, Weixiang, Petrecca, Vincenzo, Temple, Matthew J., Ni, Qingling, Shirley, Raphael, Kovacevic, Andjelka B., Nikolic, Mladen, Ilic, Dragana, Popovic, Luka C., Paolillo, Maurizio, Panda, Swayamtrupta, Ciprijanovic, Aleksandra, Richards, Gordon T.
Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DC) arranged by various LSST Scientific Collaborations (SC) that are taking place during the projects preoperational phase. The AGN Scie
Externí odkaz:
http://arxiv.org/abs/2307.04072
Autor:
Vučetić M.M., Ćiprijanović A., Pavlović M.Z., Pannuti T.G., Petrov N., Göker Ü.D., Ercan E.N.
Publikováno v:
Serbian Astronomical Journal, Vol 2015, Iss 191, Pp 67-74 (2015)
We present the detection of 16 optical supernova remnant (SNR) candidates in the nearby spiral galaxy IC342. The candidates were detected by applying the [Sii]/Hα ratio criterion on observations made with the 2 m RCC telescope at Rozhen National
Externí odkaz:
https://doaj.org/article/cd53567e26584219bb8774900381e80f
Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features. Therefore, suc
Externí odkaz:
http://arxiv.org/abs/2302.02005
The study of quasar light curves poses two problems: inference of the power spectrum and interpolation of an irregularly sampled time series. A baseline approach to these tasks is to interpolate a time series with a Damped Random Walk (DRW) model, in
Externí odkaz:
http://arxiv.org/abs/2211.10305