The complete list of my publications is available on the NASA/ADS database.
Publications with a major contribution
– [In prep. 2024] – YOLO-CIANNA: Galaxy detection with deep learning in radio data: II. MINERVA: Winning the SKA SDC2 using a generalized 3D-YOLO network, Cornu, D.; Semelin, B.; Lu, X.; Aicardi, S.; SalomĂ©, P.; Sainton, G.; Mertens, F.; Marchal, A.; Freundlich, J.; Combes F.; Tasse, C., in prep for A&A
– [in prep. 2024] – Spiral and non-spiral structure of the plane of the Milky Way, Marshall, D. J.; Montillaud, J.; CambrĂ©sy, L.; Cornu, D., in prep for A&A
– [Submitted / In rev. 2024] – YOLO-CIANNA: Galaxy detection with deep learning in radio data: I. A new YOLO-inspired source detection method applied to the SKAO SDC1, Cornu, D.; SalomĂ©, P,; Marchal, A.; Freundlich, J.; Semelin, B.; Aicardi, S.; Lu, X; Sainton, G.; Mertens, F; Combes, F.; Tasse, C., submitted to A&A, arXiv:2402.05925
– [Submitted / In rev. 2024] – The Galaxy Activity, Torus, and Outflow Survey (GATOS). V. Black hole mass estimation using machine learning, Poitevineau R., Combes F., Garcia-Burillo S., Cornu D., et al., submitted to A&A
– [In rev. 2024] – 3D extinction mapping of the Milky Way using Convolutional Neural Networks: Presentation of the method and demonstration in the Carina Arm region, Cornu, D.; Montillaud, J.; Marshall, D. J.; Robin, A. C.; Cambresy, L., [recommended for publication with minor revisions] A&A, arxiv-2201.05571
– 2023 – SKA Science Data Challenge 2: analysis and results, Harltey, P; Bonaldi, A; Braun, R; et al., MNRAS, Vol.523, Issue 2, pp.1967-1993, leading author for team MINERVA
– 2023 – Machine Learning to facilitate the study of complex organic molecules in hot cores, Kessler, N. ; Csengeri, T. ; Cornu, D. ; Bontemps, S., SF2A Proceedings 2023, 2023sf2a.conf..303K
– 2021 – A Neural Network-based methodology to select Young Stellar Object candidates from IR surveys, Cornu, D. ; Montillaud, J., A&A, Vol. 647, id.A116
– 2020 – Modeling the 3D Milky Way using Machine Learning with Gaia and infrared surveys, Cornu, D., PhD thesis, arxiv-2010.0143
– 2019 – Deep learning for the selection of Young Stellar Object candidates from IR surveys, Cornu, D.; Montillaud, J., SF2A-2019 Proceedings, pp.73-76.
Publications with a minor contribution (or collaboration papers)
– 2021 – Deciphering the evolution of the Milky Way discs : The Gaia APOGEE Kepler giant stars & Besançon Galaxy Model, Lagarde, N. ; ReylĂ©, C. ; Chiappini, C. ; Mor, R. ; Anders, F. ; Figueras, F. ; et al., A&A, Vol. 654, id.A13
– 2019 – Multi-scale analysis of the Monoceros OB 1 star-forming region. I. The dense core population, Montillaud, J.; Juvela, M.; Vastel, C.; He, J.; Liu, T.; Ristorcelli, I.; Eden, D. J.; et al., A&A, Vol. 631, id.L1
– 2019 – Multi-scale analysis of the Monoceros OB 1 star-forming region. II. Colliding filaments in the Monoceros OB1 molecular cloud, Montillaud, J.; Juvela, M.; Vastel, C.; He, J.; Liu, T.; Ristorcelli, I.; Eden, D. J. ; et al., A&A, Vol. 631, id.A3
– 2019 – SCOPE : SCUBA-2 Continuum Observations of Pre-protostellar Evolution – survey description and compact source catalog, Eden, D. J. ; Liu, T.; Kim, K.; Juvela, M. ; et al. , MNRS, Volume 485, Issue 2, pp.2895-2908