• Fast fitting of reflectivity data of growing thin films using neural networks 

      Greco, Alessandro; Starostin, Vladimir; Karapanagiotis, Christos; Hinderhofer, Alexander; Gerlach, Alexander; Pithan, Linus; Liehr, Sascha; Schreiber, Frank; Kowarik, Stefan (Journal of Applied Crystallography, 2019-11-08)
      X‐ray reflectivity (XRR) is a powerful and popular scattering technique that can give valuable insight into the growth behavior of thin films. This study shows how a simple artificial neural network model can be used to ...
    • Seasonal Carbon Dynamics in the Near‐Global Ocean 

      Keppler, L.ORCIDiD; Landschützer, P.ORCIDiD; Gruber, N.ORCIDiD; Lauvset, S. K.ORCIDiD; Stemmler, I. (Global Biogeochemical Cycles, 2020-12-23)
      The seasonal cycle represents one of the largest signals of dissolved inorganic carbon (DIC) in the ocean, yet these seasonal variations are not well established at a global scale. Here, we present the Mapped Observation‐Based ...
    • The Synergy of Data From Profiling Floats, Machine Learning and Numerical Modeling: Case of the Black Sea Euphotic Zone 

      Stanev, E. V.ORCIDiD; Wahle, K.ORCIDiD; Staneva, J.ORCIDiD (Journal of Geophysical Research: Oceans, 2022-08-24)
      Data from profiling floats in the Black Sea revealed complex temporal and spatial relationships between physical variables and oxygen, chlorophyll and the backscattering coefficient at 700 nm, as well as some limits in ...