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20212026
most citedA review of predictive uncertainty estimation with machine learning

158 citations · 341 across the 22 of their papers we have counts for

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Showing 2024Show all

4 papers · 1 filter

cs.CY2024★ 11 cited

Transforming disaster risk reduction with AI and big data: Legal and interdisciplinary perspectives

Kwok P Chun, Thanti Octavianti, Nilay Dogulu +24

Managing complex disaster risks requires interdisciplinary efforts. Breaking down silos between law, social sciences, and natural sciences is critical for all processes of disaster…

physics.soc-ph2024

Unravelling compound risks of hydrological extremes in a changing climate: Typology, methods and futures

Kwok P Chun, Thanti Octavianti, Georgia Papacharalampous +21

We have witnessed and experienced increasing compound extreme events resulting from simultaneous or sequential occurrence of multiple events in a changing climate. In addition to a…

cs.LG2024★ 2 cited

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…

cs.LG2024★ 1 cited

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…