158 citations · 341 across the 22 of their papers we have counts for
5 papers · 1 filter
Combinations of distributional regression algorithms with application in uncertainty estimation of corrected satellite precipitation products
Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis +1
To facilitate effective decision-making, precipitation datasets should include uncertainty estimates. Quantile regression with machine learning has been proposed for issuing such e…
Ensemble learning for uncertainty estimation with application to the correction of satellite precipitation products
Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis +1
Predictions in the form of probability distributions are crucial for effective decision-making. Quantile regression enables such predictions within spatial prediction settings that…
Ensemble learning for blending gridded satellite and gauge-measured precipitation data
Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis +1
Regression algorithms are regularly used for improving the accuracy of satellite precipitation products. In this context, satellite precipitation and topography data are the predic…
Comparison of tree-based ensemble algorithms for merging satellite and earth-observed precipitation data at the daily time scale
Georgia Papacharalampous, Hristos Tyralis, Anastasios Doulamis +1
Merging satellite products and ground-based measurements is often required for obtaining precipitation datasets that simultaneously cover large regions with high density and are mo…
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting
Georgia Papacharalampous, Hristos Tyralis
Probabilistic forecasting is receiving growing attention nowadays in a variety of applied fields, including hydrology. Several machine learning concepts and methods are notably rel…