Atmospheric correction is the processes of converting radiance values measured at a spectral sensor to reflectance materials in multispectral or hyperspectral image. This an important step for detecting identifying present pixel spectra. We two machine learning models atmospheric trained and tested on 100,000 batches 40 spectra converted using MODTRAN, so model learns radiative transfer physics...

• Censored data as defining characteristic of numerous domains in science. Heteroscedastic Multi-Output Gaussian Process formulated for censored regression. Generalization arbitrary likelihood functions enabled by devising a variational bound to the marginal log-likelihood. Experiments with synthetic and real-world demonstrate solution approach. When modelling observations (i.e. which value mea...

The problem of Uncertainty Quantification (UQ) is paramount importance when Machine Learning (ML) and Deep (DL) models are deployed in the real world. In context safety-critical applications, such as prediction Remaining Useful-Life (RUL) infrastructure industrial assets, relevance effective UQ approaches even higher, given potentially catastrophic consequences or substantial costs associated w...