In contrast to physics-based dynamical models are data-driven artificial intelligence (AI) approaches like deep learning. Deep learning algorithms have been a game-changer in diverse areas where large volumes of data are available, using multiple nonlinear processing layers to extract increasingly high-level … See more Sea ice is dynamically and thermodynamically coupled to the atmosphere above and ocean below42. IceNet’s 11 input climate variables (Supplementary Table 2) were chosen to capture some of the … See more Calibrated probabilities are highly desirable in probabilistic forecasting systems, with perfect calibration indicating the predicted probability equals the true probability of an event occurring. IceNet’s SIP is almost … See more We compare IceNet with SEAS546, a dynamical model from the European Centre for Medium-Range Weather Forecasts (ECMWF) with state-of-the-art sea ice prediction … See more The CMIP6 pre-training phase improves binary accuracy over the held-out years (2012–2024) by an average of 0.26%. This boost is small considering the increase in memory and computational load of the pre-training phase. … See more WebSep 11, 2024 · The study focuses on characterizing the thermo-mechanical properties of SiCf/SiC using micromechanics finite element method (FEM) and multi-scale …
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