activity
20162026
most citedGroup Sparse Regularization for Deep Neural Networks

477 citations · 1.3k across the 43 of their papers we have counts for

collaborators

45 papers

cs.LG2026

Closing the Modality Gap Aligns Group-Wise Semantics

Eleonora Grassucci, Giordano Cicchetti, Emanuele Frasca +2

In multimodal learning, CLIP has been recognized as the \textit{de facto} method for learning a shared latent space across multiple modalities, placing similar representations clos…

cs.LG2025

Generative Models for Helmholtz Equation Solutions: A Dataset of Acoustic Materials

Riccardo Fosco Gramaccioni, Christian Marinoni, Fabrizio Frezza +2

Accurate simulation of wave propagation in complex acoustic materials is crucial for applications in sound design, noise control, and material engineering. Traditional numerical so…

cs.SD2025

FoleyGRAM: Video-to-Audio Generation with GRAM-Aligned Multimodal Encoders

Riccardo Fosco Gramaccioni, Christian Marinoni, Eleonora Grassucci +3

In this work, we present FoleyGRAM, a novel approach to video-to-audio generation that emphasizes semantic conditioning through the use of aligned multimodal encoders. Building on…

cs.LG2025

Training-Free Multimodal Guidance for Video to Audio Generation

Eleonora Grassucci, Giuliano Galadini, Giordano Cicchetti +3

Video-to-audio (V2A) generation aims to synthesize realistic and semantically aligned audio from silent videos, with potential applications in video editing, Foley sound design, an…

cs.LG2025

Semantic Compression via Multimodal Representation Learning

Eleonora Grassucci, Giordano Cicchetti, Aurelio Uncini +1

Multimodal representation learning produces high-dimensional embeddings that align diverse modalities in a shared latent space. While this enables strong generalization, it also in…

cs.CV2025★ 2 cited

Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution

Luigi Sigillo, Christian Bianchi, Aurelio Uncini +1

Image Super-Resolution is a fundamental problem in computer vision with broad applications spacing from medical imaging to satellite analysis. The ability to reconstruct high-resol…