Georgia Papacharalampous

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 22

Top Topics

Learning Algorithm

Machine Learning

Variable Selection

Top Venues

Neural Comput. Appl.

Artif. Intell. Rev.

Publications

Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis, Anastasios Doulamis
Uncertainty estimation in satellite precipitation spatial prediction by combining distributional regression algorithms. CoRR (2024)
Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis, Anastasios Doulamis
Uncertainty estimation in spatial interpolation of satellite precipitation with ensemble learning. CoRR (2024)
Hristos Tyralis, Georgia Papacharalampous
A review of predictive uncertainty estimation with machine learning. Artif. Intell. Rev. 57 (4) (2024)
Georgia Papacharalampous, Hristos Tyralis, Anastasios D. Doulamis, Nikolaos Doulamis
Comparison of machine learning algorithms for merging gridded satellite and earth-observed precipitation data. CoRR (2023)
Hristos Tyralis, Georgia Papacharalampous, Nilay Dogulu, Kwok P. Chun
Deep Huber quantile regression networks. CoRR (2023)
Hristos Tyralis, Georgia Papacharalampous, Nikolaos D. Doulamis, Anastasios Doulamis
Merging satellite and gauge-measured precipitation using LightGBM with an emphasis on extreme quantiles. CoRR (2023)
Georgia Papacharalampous, Hristos Tyralis, Anastasios D. Doulamis, Nikolaos Doulamis
Comparison of tree-based ensemble algorithms for merging satellite and earth-observed precipitation data at the daily time scale. CoRR (2023)
Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis, Anastasios Doulamis
Ensemble Learning for Blending Gridded Satellite and Gauge-Measured Precipitation Data. Remote. Sens. 15 (20) (2023)
Georgia Papacharalampous, Hristos Tyralis, Nikolaos D. Doulamis, Anastasios D. Doulamis
Ensemble learning for blending gridded satellite and gauge-measured precipitation data. CoRR (2023)
Hristos Tyralis, Georgia Papacharalampous, Nikolaos Doulamis, Anastasios D. Doulamis
Merging Satellite and Gauge-Measured Precipitation Using LightGBM With an Emphasis on Extreme Quantiles. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 16 (2023)
Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis, Anastasios Doulamis
Machine learning for uncertainty estimation in fusing precipitation observations from satellites and ground-based gauges. CoRR (2023)
Hristos Tyralis, Georgia Papacharalampous
A review of probabilistic forecasting and prediction with machine learning. CoRR (2022)
Georgia Papacharalampous, Hristos Tyralis
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting. CoRR (2022)
Hristos Tyralis, Georgia Papacharalampous
Boosting algorithms in energy research: a systematic review. Neural Comput. Appl. 33 (21) (2021)
Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis
Super ensemble learning for daily streamflow forecasting: large-scale demonstration and comparison with multiple machine learning algorithms. Neural Comput. Appl. 33 (8) (2021)
Georgia Papacharalampous, Andreas Langousis
Probabilistic water demand forecasting using quantile regression algorithms. CoRR (2021)
Georgia Papacharalampous, Hristos Tyralis, Ilias G. Pechlivanidis, Salvatore Grimaldi, Elena Volpi
Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale. CoRR (2021)
Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis, Simon Michael Papalexiou
Explanation and Probabilistic Prediction of Hydrological Signatures with Statistical Boosting Algorithms. Remote. Sens. 13 (3) (2021)
Hristos Tyralis, Georgia Papacharalampous
Boosting algorithms in energy research: A systematic review. CoRR (2020)
Georgia Papacharalampous, Hristos Tyralis
Hydrological time series forecasting using simple combinations: Big data testing and investigations on one-year ahead river flow predictability. CoRR (2020)
Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis
Super learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms. CoRR (2019)
Hristos Tyralis, Georgia Papacharalampous
Variable Selection in Time Series Forecasting Using Random Forests. Algorithms 10 (4) (2017)