Patch-Based Deep Kernel Learning for Data Assimilation and Bias Correction with Extremely Sparse Observations
A hybrid framework that couples a convolutional neural network with a learnable-kernel Gaussian Process to jointly perform DA and bias correction from extremely sparse observations is proposed, outperforms 3D-Var, a classical GP and a competing DL model, while reducing inference time.
Emanuele Mele, A. Coluccia, M. Cafaro et al.
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