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| RX J0529.0+0934 , the SIMBAD biblio (37 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.18CEST02:04:57 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
|
1997A&A...323..739B |
1540 | 68 | Radio-loud AGN in the northern ROSAT All-Sky Survey. II. Multi-frequency properties of unidentified sources. | BRINKMANN W., SIEBERT J., FEIGELSON E.D., et al. | |||||
|
1998A&AS..132..341M |
93 | 82 | Identification of selected sources from the ROSAT Galactic Plane Survey. I. | MOTCH C., GUILLOUT P., HABERL F., et al. | |||||
|
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. | ||
|
2012ApJS..199...31N |
15 | D | 1 | 2260 | 1282 | Fermi Large Area Telescope second source catalog. | NOLAN P.L., ABDO A.A., ACKERMANN M., et al. | ||
|
2012MNRAS.424.2832L |
15 | D | 1 | 1877 | 43 | Application of the Gaussian mixture model in pulsar astronomy – pulsar classification and candidates ranking for the Fermi 2FGL catalogue. | LEE K.J., GUILLEMOT L., YUE Y.L., et al. | ||
|
2013MNRAS.428..220H |
15 | D | 1 | 473 | 19 | Gamma-ray active galactic nucleus type through machine-learning algorithms. | HASSAN T., MIRABAL N., CONTRERAS J.L., et al. | ||
|
2013ApJS..209...34A |
15 | D | 1 | 553 | 210 | The first Fermi-LAT catalog of sources above 10 GeV. | ACKERMANN M., AJELLO M., ALLAFORT A., et al. | ||
|
2015ApJS..217....2M |
16 | D | 2 | 2199 | 42 | Refining the associations of the Fermi large area telescope source catalogs. | MASSARO F., D'ABRUSCO R., LANDONI M., et al. | ||
|
2015ApJS..218...23A |
16 | D | 1 | 3140 | 1411 | Fermi Large Area Telescope third source catalog. | ACERO F., ACKERMANN M., AJELLO M., et al. | ||
|
2015ApJ...810...14A |
16 | D | 1 | 1890 | 513 | The third catalog of active galactic nuclei detected by the Fermi large area telescope. | ACKERMANN M., AJELLO M., ATWOOD W.B., et al. | ||
|
2016ApJ...820....8S |
16 | D | 1 | 3047 | 91 | Classification and ranking of Fermi LAT gamma-ray sources from the 3FGL catalog using machine learning techniques. | SAZ PARKINSON P.M., XU H., YU P.L.H., et al. | ||
|
2016ApJS..226...20F |
16 | D | 1 | 1394 | 122 | The spectral energy distributions of Fermi blazars. | FAN J.H., YANG J.H., LIU Y., et al. | ||
|
2016MNRAS.462.3180C |
16 | D | 1 | 576 | 21 | Blazar flaring patterns (B-FlaP) classifying blazar candidate of uncertain type in the third Fermi-LAT catalogue by artificial neural networks. | CHIARO G., SALVETTI D., LA MURA G., et al. | ||
| 2016A&A...594A..60L | 39 | X | 1 | 89 | 6 | VLBA observations of radio faint Fermi-LAT sources above 10 GeV. | LICO R., GIROLETTI M., ORIENTI M., et al. | ||
|
2017A&A...598A..17C |
16 | D | 1 | 1692 | 30 | 2WHSP: A multi-frequency selected catalogue of high energy and very high energy γ-ray blazars and blazar candidates. | CHANG Y.-L., ARSIOLI B., GIOMMI P., et al. | ||
|
2017A&A...602A..86L |
16 | D | 1 | 1082 | 1 | Research and characterisation of blazar candidates among the Fermi/LAT 3FGL catalogue using multivariate classifications. | LEFAUCHEUR J. and PITA S. | ||
|
2017ApJS..232...18A |
16 | D | 1584 | 263 | 3FHL: the Third Catalog of Hard Fermi-LAT Sources. | AJELLO M., ATWOOD W.B., BALDINI L., et al. | |||
|
2018ApJS..235...39C |
16 | D | 1 | 1395 | 63 | On the jet properties of γ-ray-loud active galactic nuclei. | CHEN L. | ||
|
2018ApJS..237...32A |
16 | D | 1 | 2605 | 130 | The search for spatial extension in high-latitude sources detected by the Fermi Large Area Telescope. | ACKERMANN M., AJELLO M., BALDINI L., et al. | ||
|
2018RAA....18...56K |
16 | D | 1 | 1421 | 3 | On the intrinsic shape of the gamma-ray spectrum for Fermi blazars. | KANG S.-J., WU Q., ZHENG Y.-G., et al. | ||
|
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. | ||
|
2019MNRAS.490.4770K |
16 | D | 1 | 567 | ~ | Optimizing neural network techniques in classifying Fermi-LAT gamma-ray sources. | KOVACEVIC M., CHIARO G., CUTINI S., 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.505.5853G | 17 | D | 2 | 5834 | ~ | Artificial Neural Network classification of 4FGL sources. | GERMANI S., TOSTI G., LUBRANO P., et al. | ||
| 2022MNRAS.512..137N | 528 | D | X F | 12 | 27 | 7 | Hunting extreme BL Lacertae blazars with Fermi-Large Area Telescope. | NIEVAS ROSILLO M., DOMINGUEZ A., CHIARO G., et al. | |
|
2022A&A...660A..87B |
17 | D | 2 | 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..262...18Y |
17 | D | 1 | 2709 | 8 | The Spectral Energy Distributions for 4FGL Blazars. | YANG J.H., FAN J.H., LIU Y., 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. | ||
|
2023ApJS..268...23F |
17 | D | 1 | 2708 | ~ | Characterizing the Emission Region Properties of Blazars. | FAN J., XIAO H., YANG W., 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. | |||||
| 2024ApJS..275...11Z | 18 | D | 1 | 235 | ~ | Chasing the Neutrino Blazar Candidates. | ZHU J., CAO H., XIAO H., et al. | ||
| 2025PASP..137f4105D | 19 | D | 1 | 290 | ~ | Improved Fermi Blazar Candidate Classifications with SRG/eROSITA X-Ray Counterparts Using Machine Learning. | DING J. and RODRIGUEZ A.C. |