Transferring climate change physical knowledge
2025, Proceedings Of The National Academy Of Sciences, doi: 10.1073/pnas.2413503122
Filtering by author: Immorlano Francesco
End-to-End Workflows for Climate Science: Integrating HPC Simulations, Big Data Processing, and Machine Learning
Elia D., Scardigno S., Ejarque J., D'Anca A., Accarino G., Scoccimarro E., Donno D., Peano D., Immorlano F., Aloisio G.
2023, Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W '23), Association for Computing Machinery, New York, NY, USA, 2042–2052, doi: 10.1145/3624062.3624283
An ensemble machine learning approach for tropical cyclone localization and tracking from ERA5 reanalysis data
Accarino G., Donno D., Immorlano F., Elia D., Aloisio G.
2023, Earth and Space Science, Volume 10, Issue 11, doi: 10.1029/2023EA003106
An Artificial Neural Network-based approach for predicting the COVID-19 daily effective reproduction number Rt in Italy
Gatto A., Aloisi V., Accarino G., Immorlano F., Chiarelli M., Aloisio G.
2022, AI, Volume 3, Issue 1, 146-163, doi: 10.3390/ai3010009
MSG-GAN-SD: A Multi-Scale Gradients GAN for Statistical Downscaling of 2-Meter Temperature over the EURO-CORDEX Domain
Accarino G., Chiarelli M., Immorlano F., Aloisi V., Gatto A., Aloisio G.
2021, AI, 2(4), 600-620;, doi: 10.3390/ai2040036