Antonios Mamalakis
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Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database
A Langousis, A Mamalakis, M Puliga, R Deidda
Water Resources Research 52 (4), 2659-2681, 2016
Zonally contrasting shifts of the tropical rain belt in response to climate change
A Mamalakis, JT Randerson, JY Yu, MS Pritchard, G Magnusdottir, ...
Nature climate change 11 (2), 143-151, 2021
Neural network attribution methods for problems in geoscience: A novel synthetic benchmark dataset
A Mamalakis, I Ebert-Uphoff, EA Barnes
Environmental Data Science 1, e8, 2022
A new interhemispheric teleconnection increases predictability of winter precipitation in southwestern US
A Mamalakis, JY Yu, JT Randerson, A AghaKouchak, ...
Nature communications 9 (1), 2332, 2018
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience
A Mamalakis, EA Barnes, I Ebert-Uphoff
Artificial Intelligence for the Earth Systems 1 (4), e220012, 2022
A parametric approach for simultaneous bias correction and high‐resolution downscaling of climate model rainfall
A Mamalakis, A Langousis, R Deidda, M Marrocu
Water Resources Research 53 (3), 2149-2170, 2017
Assessing the relative effectiveness of statistical downscaling and distribution mapping in reproducing rainfall statistics based on climate model results
A Langousis, A Mamalakis, R Deidda, M Marrocu
Water Resources Research 52 (1), 471-494, 2016
Explainable artificial intelligence in meteorology and climate science: Model fine-tuning, calibrating trust and learning new science
A Mamalakis, I Ebert-Uphoff, EA Barnes
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2020
Carefully choose the baseline: Lessons learned from applying XAI attribution methods for regression tasks in geoscience
A Mamalakis, EA Barnes, I Ebert-Uphoff
Artificial Intelligence for the Earth Systems 2 (1), e220058, 2023
Underestimated MJO variability in CMIP6 models
PVV Le, C Guilloteau, A Mamalakis, E Foufoula‐Georgiou
Geophysical research letters 48 (12), e2020GL092244, 2021
A multivariate probabilistic framework for tracking the intertropical convergence zone: Analysis of recent climatology and past trends
A Mamalakis, E Foufoula‐Georgiou
Geophysical Research Letters 45 (23), 13,080-13,089, 2018
Graph-guided regularized regression of pacific ocean climate variables to increase predictive skill of southwestern us winter precipitation
A Stevens, R Willett, A Mamalakis, E Foufoula-Georgiou, A Tejedor, ...
Journal of climate 34 (2), 737-754, 2021
Reply to: A critical examination of a newly proposed interhemispheric teleconnection to Southwestern US winter precipitation
A Mamalakis, JY Yu, JT Randerson, A AghaKouchak, ...
Nature communications 10 (1), 2918, 2019
Rotated spectral principal component analysis (rsPCA) for identifying dynamical modes of variability in climate systems
C Guilloteau, A Mamalakis, L Vulis, PVV Le, TT Georgiou, ...
Journal of climate 34 (2), 715-736, 2021
Climate-driven changes in the predictability of seasonal precipitation
PVV Le, JT Randerson, R Willett, S Wright, P Smyth, C Guilloteau, ...
Nature communications 14 (1), 3822, 2023
Hotspots of predictability: Identifying regions of high precipitation predictability at seasonal timescales from limited time series observations
A Mamalakis, A AghaKouchak, JT Randerson, E Foufoula‐Georgiou
Water resources research 58 (5), e2021WR031302, 2022
Artificial Intelligence for Prediction of Climate Extremes: State of the art, challenges and future perspectives
S Materia, LP García, C van Straaten, A Mamalakis, L Cavicchia, ...
arXiv preprint arXiv:2310.01944, 2023
Links of climate variability and change with regional hydroclimate: Predictability, trends, and physical mechanisms on seasonal to decadal scales
A Mamalakis
University of California, Irvine, 2020
Estimation of seawater retreat timescales in homogeneous and confined coastal aquifers based on dimensional analysis
A Mamalakis, V Kaleris
Hydrological Sciences Journal 64 (2), 190-209, 2019
Using explainable artificial intelligence to quantify “climate distinguishability” after stratospheric aerosol injection
A Mamalakis, EA Barnes, JW Hurrell
Geophysical Research Letters 50 (20), e2023GL106137, 2023
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