Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction
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Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction
Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome ...
Apr 8, 2021
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