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Non-negative decomposition of linear relationships: Application to multi-source ocean remote sensing data.

, , , , and . ICASSP, page 4179-4183. IEEE, (2016)

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Long Term Object Drift Forecast in the Ocean with Tide and Wind., , and . Multiscale Modeling & Simulation, 5 (2): 514-531 (2006)Modeling process asymmetries with Laplace moving average., , and . Comput. Stat. Data Anal., (2015)Non-negative decomposition of linear relationships: Application to multi-source ocean remote sensing data., , , , and . ICASSP, page 4179-4183. IEEE, (2016)Learning the spatio-temporal relationship between wind and significant wave height using deep learning., , , and . CoRR, (2022)Characterization of Time-Varying Regimes in Remote Sensing Time Series: Application to the Forecasting of Satellite-Derived Suspended Matter Concentrations., , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 8 (1): 406-417 (2015)Non-negative decomposition of geophysical dynamics., , , and . ESANN, (2017)Ocean surface current retrieval using a non homogeneous Markov-switching multi-regime model., , and . ICIP, page 2968-2972. IEEE, (2014)Hidden surface dynamical modes and SSH retrievals from a joint analysis of altimetry and microwave SST., , and . IGARSS, page 5123-5125. IEEE, (2014)Markov-switching autoregressive models for wind time series., and . Environ. Model. Softw., (2012)A Multivariate Regression Approach to Adjust AATSR Sea Surface Temperature to In Situ Measurements., , , , and . IEEE Geosci. Remote. Sens. Lett., 6 (1): 8-12 (2009)