3 papers
stat.AP2026
Controlling Ensemble Variance in Diffusion Models: An Application for Reanalyses Downscaling
Fabio Merizzi, Davide Evangelista, Harilaos Loukos
In recent years, diffusion models have emerged as powerful tools for generating ensemble members in meteorology. In this work, we demonstrate how a Denoising Diffusion Implicit Mod…
cs.LG2025
On the flow matching interpretability
Francesco Pivi, Simone Gazza, Davide Evangelista +2
Generative models based on flow matching have demonstrated remarkable success in various domains, yet they suffer from a fundamental limitation: the lack of interpretability in the…
cs.CL2025
Language Models Are Implicitly Continuous
Samuele Marro, Davide Evangelista, X. Angelo Huang +3
Language is typically modelled with discrete sequences. However, the most successful approaches to language modelling, namely neural networks, are continuous and smooth function ap…