58 citations · 93 across the 6 of their papers we have counts for
6 papers
ByteStorm: a multi-step data-driven approach for Tropical Cyclones detection and tracking
Davide Donno, Donatello Elia, Gabriele Accarino +3
Accurate tropical cyclones (TCs) tracking represents a critical challenge in the context of weather and climate science. Traditional tracking schemes mainly rely on subjective thre…
MedFormer: a data-driven model for forecasting the Mediterranean Sea
Italo Epicoco, Davide Donno, Gabriele Accarino +14
Accurate ocean forecasting is essential for supporting a wide range of marine applications. Recent advances in artificial intelligence have highlighted the potential of data-driven…
Improving Oil Slick Trajectory Simulations with Bayesian Optimization
Gabriele Accarino, Marco M. De Carlo, Igor Atake +8
Accurate simulations of oil spill trajectories are essential for supporting practitioners' response and mitigating environmental and socioeconomic impacts. Numerical models, such a…
Transferring climate change physical knowledge
Francesco Immorlano, Veronika Eyring, Thomas le Monnier de Gouville +5
Precise and reliable climate projections are required for climate adaptation and mitigation, but Earth system models still exhibit great uncertainties. Several approaches have been…
An Ensemble Machine Learning Approach for Tropical Cyclone Detection Using ERA5 Reanalysis Data
Gabriele Accarino, Davide Donno, Francesco Immorlano +2
Tropical Cyclones (TCs) are counted among the most destructive phenomena that can be found in nature. Every year, globally an average of 90 TCs occur over tropical waters, and glob…
Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence
Jorge Ejarque, Rosa M. Badia, Loïc Albertin +34
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The co…