11 citations · 14 across the 6 of their papers we have counts for
7 papers
Revisiting Diffusion Fine-Tuning for Unsupervised Domain Adaptation
Xuan Qi, Yi Wei, Daniele Berardini +2
Diffusion-based unsupervised domain adaptation (UDA) improves cross-domain transfer by generating target-specific synthetic data for downstream adaptation. Existing methods are lar…
VT-DUDA: Visual Token Conditioning for Diffusion-guided Unsupervised Domain Adaptation
Xuan Qi, Daniele Berardini, Dario Serez +2
Unsupervised domain adaptation (UDA) aims to learn a target-domain classifier from labeled source data and unlabeled target data under distribution shift. Recent diffusion-based UD…
ELEVATE: Designing Human-Centered GenAI Virtual Tutors for Scalable and Inclusive Education
Lorenzo Stacchio, Michele Giordano, Daniele Berardini +2
The advent of Generative Artificial Intelligence (GenAI), and in particular Large Language Models (LLMs), is reshaping educational practice, while intensifying ethical debate about…
Distribution Alignment for One-Shot Federated Learning via Optimal Transport
Daniele Berardini, Vito Paolo Pastore, Vittorio Murino
One-Shot Federated Learning (OSFL) addresses extreme communication regimes in which clients interact with the server only once, amplifying the impact of heterogeneous client data d…
A preliminary study on continual learning in computer vision using Kolmogorov-Arnold Networks
Alessandro Cacciatore, Valerio Morelli, Federica Paganica +3
Deep learning has long been dominated by multi-layer perceptrons (MLPs), which have demonstrated superiority over other optimizable models in various domains. Recently, a new alter…
A store-and-forward cloud-based telemonitoring system for automatic assessing dysarthria evolution in neurological diseases from video-recording analysis
Lucia Migliorelli, Daniele Berardini, Kevin Cela +4
Background and objectives: Patients suffering from neurological diseases may develop dysarthria, a motor speech disorder affecting the execution of speech. Close and quantitative m…
Deep learning-based approaches for human motion decoding in smart walkers for rehabilitation
Carolina Gonçalves, João M. Lopes, Sara Moccia +3
Gait disabilities are among the most frequent worldwide. Their treatment relies on rehabilitation therapies, in which smart walkers are being introduced to empower the user's recov…