activity
20072023
most citedMetis: the Solar Orbiter visible light and ultraviolet coronal imager

190 citations · 1.2k across the 44 of their papers we have counts for

collaborators

51 papers

astro-ph.SR2023

Coronal Heating Rate in the Slow Solar Wind

Daniele Telloni, Marco Romoli, Marco Velli +59

This Letter reports the first observational estimate of the heating rate in the slowly expanding solar corona. The analysis exploits the simultaneous remote and local observations…

cs.CV2023★ 4 cited

Fast Inference in Denoising Diffusion Models via MMD Finetuning

Emanuele Aiello, Diego Valsesia, Enrico Magli

Denoising Diffusion Models (DDMs) have become a popular tool for generating high-quality samples from complex data distributions. These models are able to capture sophisticated pat…

cs.CV2022★ 17 cited

Rethinking the compositionality of point clouds through regularization in the hyperbolic space

Antonio Montanaro, Diego Valsesia, Enrico Magli

Point clouds of 3D objects exhibit an inherent compositional nature where simple parts can be assembled into progressively more complex shapes to form whole objects. Explicitly cap…

cs.CV2022★ 19 cited

Cross-modal Learning for Image-Guided Point Cloud Shape Completion

Emanuele Aiello, Diego Valsesia, Enrico Magli

In this paper we explore the recent topic of point cloud completion, guided by an auxiliary image. We show how it is possible to effectively combine the information from the two mo…

eess.IV2022

Exploring the solution space of linear inverse problems with GAN latent geometry

Antonio Montanaro, Diego Valsesia, Enrico Magli

Inverse problems consist in reconstructing signals from incomplete sets of measurements and their performance is highly dependent on the quality of the prior knowledge encoded via…

eess.IV2022

Super-resolved multi-temporal segmentation with deep permutation-invariant networks

Diego Valsesia, Enrico Magli

Multi-image super-resolution from multi-temporal satellite acquisitions of a scene has recently enjoyed great success thanks to new deep learning models. In this paper, we go beyon…