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| 1RXS J034424.5+343016 , the SIMBAD biblio (19 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.19CEST07:47:19 |
| Bibcode/DOI | Score |
in Title|Abstract| Keywords |
in a table | in teXt, Caption, ... | Nb occurence | Nb objects in ref |
Citations (from ADS) |
Title | First 3 Authors |
|---|---|---|---|---|---|---|---|---|---|
|
2009ApJS..184..138H |
15 | D | 1 | 20623 | 68 | XID II: statistical cross-association of ROSAT bright source catalog X-ray sources with 2MASS point source catalog near-infrared sources. | HAAKONSEN C.B. and RUTLEDGE R.E. | ||
|
2019A&A...632A..77C |
16 | D | 1 | 2017 | 54 | The 3HSP catalogue of extreme and high-synchrotron peaked blazars. | CHANG Y.-L., ARSIOLI B., GIOMMI P., et al. | ||
|
2019ApJ...887..134K |
16 | D | 1 | 1314 | ~ | Evaluating the classification of Fermi BCUs from the 4FGL catalog using machine learning. | KANG S.-J., LI E., OU W., et al. | ||
|
2020MNRAS.493.1926K |
16 | D | 1 | 1330 | ~ | Classification of blazar candidates of uncertain type from the Fermi LAT 8-yr source catalogue with an artificial neural network. | KOVACEVIC M., CHIARO G., CUTINI S., et al. | ||
|
2020ApJS..247...33A |
16 | D | 1 | 5175 | 880 | Fermi Large Area Telescope fourth source catalog. | ABDOLLAHI S., ACERO F., ACKERMANN M., et al. | ||
|
2020ApJ...892..105A |
16 | D | 1 | 3421 | 235 | The fourth catalog of active galactic nuclei detected by the Fermi Large Area Telescope. | AJELLO M., ANGIONI R., AXELSSON M., et al. | ||
| 2021MNRAS.504.3338P | 268 | D | X F | 6 | 99 | ~ | The spectra of IceCube neutrino candidate sources - I. Optical spectroscopy of blazars. | PAIANO S., FALOMO R., TREVES A., et al. | |
| 2021MNRAS.505.5853G | 17 | D | 2 | 5834 | ~ | Artificial Neural Network classification of 4FGL sources. | GERMANI S., TOSTI G., LUBRANO P., et al. | ||
| 2022MNRAS.510.2671P | 17 | D | 2 | 69 | 12 | The spectra of IceCube neutrino (SIN) candidate sources - II. Source characterization. | PADOVANI P., GIOMMI P., FALOMO R., et al. | ||
|
2022A&A...660A..87B |
17 | D | 1 | 6191 | 10 | Machine learning methods for constructing probabilistic Fermi-LAT catalogs. | BHAT A. and MALYSHEV D. | ||
|
2022ApJS..260...53A |
17 | D | 1 | 6710 | 133 | Incremental Fermi Large Area Telescope Fourth Source Catalog. | ABDOLLAHI S., ACERO F., BALDINI L., et al. | ||
|
2022ApJS..263...24A |
17 | D | 1 | 3828 | 15 | The Fourth Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope: Data Release 3. | AJELLO M., BALDINI L., BALLET J., et al. | ||
| 2023MNRAS.523.4120D | 17 | D | 1 | 420 | ~ | Hybrid deep learning for blazar classification and correlation search with neutrinos. | DING J., HUANG Y., LI X.-D., et al. | ||
| 2023MNRAS.526..661K | 17 | D | 6 | 55 | ~ | The spectra of IceCube Neutrino (SIN) candidate sources - IV. Spectral energy distributions and multiwavelength variability. | KARL M., PADOVANI P. and GIOMMI P. | ||
| 2024MNRAS.527.4763D | 18 | D | 2 | 353 | ~ | Constraints on redshifts of blazars from extragalactic background light attenuation using Fermi-LAT data. | DOMINGUEZ A., LAINEZ M., PALIYA V.S., et al. | ||
| 2024MNRAS.530.2282D | 1940 | ~ | Predicting conditional probability distributions of redshifts of Active Galactic Nuclei using Hierarchical Correlation Reconstruction. | DUDA J. and BHATTA G. | |||||
| 2024A&A...689A.147R | 18 | D | 3 | 54 | ~ | The Spectra of IceCube Neutrino (SIN) candidate sources V. Modeling and interpretation of multiwavelength and neutrino data. | RODRIGUES X., KARL M., PADOVANI P., et al. | ||
| 2025ApJ...994..136K | 19 | D | 1 | 37 | ~ | Impact of Multimessenger Spectral Modeling on Blazar-Neutrino Associations. | KUHLMANN J. and CAPEL F. | ||
| 2026ApJ...997...19S | 20 | D | 4 | 74 | ~ | Discovering High-z BL Lacs Using Swift/UVOT and SARA Observations with the Dropout Technique. | SHENG Y., IMAM K., KAUR A., et al. |