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20222025
most citedPrecipitation nowcasting with generative diffusion models

13 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Evaluating Adversarial Attacks on Federated Learning for Temperature Forecasting

Karina Chichifoi, Fabio Merizzi, Michele Colajanni

Deep learning and federated learning (FL) are becoming powerful partners for next-generation weather forecasting. Deep learning enables high-resolution spatiotemporal forecasts tha…

cs.CV2024★ 1 cited

Deep Learning for Sea Surface Temperature Reconstruction under Cloud Occlusion

Andrea Asperti, Ali Aydogdu, Angelo Greco +6

Sea Surface Temperature (SST) reconstructions from satellite images affected by cloud gaps have been extensively documented in the past three decades. Here we describe several Mach…

cs.LG2024★ 2 cited

Wind speed super-resolution and validation: from ERA5 to CERRA via diffusion models

Fabio Merizzi, Andrea Asperti, Stefano Colamonaco

The Copernicus Regional Reanalysis for Europe, CERRA, is a high-resolution regional reanalysis dataset for the European domain. In recent years it has shown significant utility acr…

cs.LG2023★ 13 cited

Precipitation nowcasting with generative diffusion models

Andrea Asperti, Fabio Merizzi, Alberto Paparella +3

In recent years traditional numerical methods for accurate weather prediction have been increasingly challenged by deep learning methods. Numerous historical datasets used for shor…

cs.CV2022

Image Embedding for Denoising Generative Models

Andrea Asperti, Davide Evangelista, Samuele Marro +1

Denoising Diffusion models are gaining increasing popularity in the field of generative modeling for several reasons, including the simple and stable training, the excellent genera…