A data-fusion technique for forecasting of absolute sea levels in the Baltic SeaRajabi-Kiasari, Saeed; Delpeche-Ellmann, Nicole Camille; Ellmann, Artu2023 Machine Learning And Data Analysis In Oceanography, University of Liège, Belgium2023 A data-fusion technique for forecasting of absolute sea levels in the Baltic Sea Forecasting of absolute dynamic topography by utilizing machine learning with synergy of satellite altimetry dataDelpeche-Ellmann, Nicole Camille; Rajabi-Kiasari, Saeed; Ellmann, Artu13th Coastal Altimetry Workshop & Coastal Altimetry Training, 6-10 February 2023, Universidad de Cádiz, Spain : abstract2023 / p. 42 https://www.coastalaltimetry.org/NikalWebsitePortal/coastal-altimetry-workshop/esa/ExtraContent/ContentSubPage?page=8&subPage=3 Forecasting of absolute dynamic topography using deep learning algorithm with application to the Baltic SeaRajabi-Kiasari, Saeed; Delpeche-Ellmann, Nicole Camille; Ellmann, ArtuComputers & geosciences2023 / art. 105406, 16 p. : ill https://doi.org/10.1016/j.cageo.2023.105406 Machine learning Forecasting of Absolute Dynamic Topography in the Baltic SeaRajabi-Kiasari, Saeed; Delpeche-Ellmann, Nicole Camille; Ellmann, ArtuNordic Geodetic Commission General Assembly 2022 in Copenhagen : Poster Session2022 / 36 l. https://medialib.cmcdn.dk/medialibrary/010C1367-E991-4A33-AB10-1953247E9C23/530AEABD-3A25-ED11-84B6-00155D0B0940.pdf Reconstruction of dynamic topography using cyclostationary empirical orthogonal functions in the Baltic SeaMostafavi, Majid; Rajabi-Kiasari, Saeed; Jahanmard, Vahidreza; Delpeche-Ellmann, Nicole Camille; Ellmann, ArtuNordic Geodetic Commission General Assembly 2022 in Copenhagen : Poster Session2022 / 25 l. https://medialib.cmcdn.dk/medialibrary/010C1367-E991-4A33-AB10-1953247E9C23/530AEABD-3A25-ED11-84B6-00155D0B0940.pdf Validation of conventional and retracked Sentinel-3 observations along the Norwegian coastMostafavi, Majid; Jahanmard, Vahidreza; Rajabi-Kiasari, Saeed; Delpeche-Ellmann, Nicole Camille; Ellmann, ArtuNordic Geodetic Commission General Assembly 2022 in Copenhagen : Poster Session2022 / 27 l. https://medialib.cmcdn.dk/medialibrary/010C1367-E991-4A33-AB10-1953247E9C23/530AEABD-3A25-ED11-84B6-00155D0B0940.pdf