Explainable AI for Car Crash Detection using Multivariate Time Series. - Lorenzo Tronchin; Rosa Sicilia; Ermanno Cordelli; Lorenzo Ricciardi Celsi; Daniele Maccagnola; Massimo Natale; Paolo Soda (ICCI*CC, 2021)

Evaluating GANs in Medical Imaging. - Lorenzo Tronchin; Rosa Sicilia; Ermanno Cordelli; Sara Ramella; Paolo Soda (DGM4MICCAI/DALI@MICCAI, 2021)

A Comparative Study Between Paired And Unpaired Image Quality Assessment In Low-Dose CT Denoising. - Francesco Di Feola; Lorenzo Tronchin; Paolo Soda (CBMS, 2023)

Making AI trustworthy in multimodal and healthcare scenarios. - Ermanno Cordelli; Valerio Guarrasi; Giulio Iannello; Filippo Ruffini; Rosa Sicilia; Paolo Soda; Lorenzo Tronchin (Ital-IA, 2023)

Building an AI-Enabled Metaverse for Intelligent Healthcare: Opportunities and Challenges. - Valerio Guarrasi; Lorenzo Tronchin; Camillo Maria Caruso; Aurora Rofena; Guido Manni; Fatih Aksu; Domenico Paolo; Giulio Iannello; Rosa Sicilia; Ermanno Cordelli; Paolo Soda (Ital-IA, 2023)

LatentAugment: Data Augmentation via Guided Manipulation of GAN's Latent Space. - Lorenzo Tronchin; Minh H. Vu; Paolo Soda; Tommy Löfstedt (CoRR, 2023)

Benchmarking GAN-Based vs Classical Data Augmentation on Biomedical Images. - Massimiliano Mantegna; Lorenzo Tronchin; Matteo Tortora; Paolo Soda (ICPR (Workshops and Challenges, 2), 2024)

Virtual Scanner: Leveraging Resilient Generative AI for Radiological Imaging in the Era of Medical Digital Twins. - Carolina Adornato; Cecilia Assolito; Ermanno Cordelli; Francesco Di Feola; Valerio Guarrasi; Giulio Iannello; Lorenzo Marcoccia; Elena Mulero Ayllon; Rebecca Restivo; Aurora Rofena; Rosa Sicilia; Paolo Soda; et al. (Ital-IA, 2024)

Multi-Dataset Multi-Task Learning for COVID-19 Prognosis. - Filippo Ruffini; Lorenzo Tronchin; Zhuoru Wu; Wenting Chen; Paolo Soda; Linlin Shen; Valerio Guarrasi (MICCAI (12), 2024)

Translating Image XAI to Multivariate Time Series. - Lorenzo Tronchin; Ermanno Cordelli; Lorenzo Ricciardi Celsi; Daniele Maccagnola; Massimo Natale; Paolo Soda; Rosa Sicilia (IEEE Access, 2024)

Multi-Scale Texture Loss for CT denoising with GANs. - Francesco Di Feola; Lorenzo Tronchin; Valerio Guarrasi; Paolo Soda (CoRR, 2024)

Multimodal explainability via latent shift applied to COVID-19 stratification. - Valerio Guarrasi; Lorenzo Tronchin; Domenico Albano; Eliodoro Faiella; Deborah Fazzini; Domiziana Santucci; Paolo Soda (Pattern Recognit., 2024)

Whole-Body Image-to-Image Translation for a Virtual Scanner in a Healthcare Digital Twin. - Valerio Guarrasi; Francesco Di Feola; Rebecca Restivo; Lorenzo Tronchin; Paolo Soda (CBMS, 2025)

From Promise to Practice: A Study of Common Pitfalls Behind the Generalization Gap in Machine Learning. - Saeideh Ghanbari Azar; Lorenzo Tronchin; Attila Simkó; Tufve Nyholm; Tommy Löfstedt (Trans. Mach. Learn. Res., 2025)

Using Synthetic Images to Augment Small Medical Image Datasets. - Minh H. Vu; Lorenzo Tronchin; Tufve Nyholm; Tommy Löfstedt (CoRR, 2025)

Beyond a Single Mode: GAN Ensembles for Diverse Medical Data Generation. - Lorenzo Tronchin; Tommy Löfstedt; Paolo Soda; Valerio Guarrasi (CoRR, 2025)

Beyond the Generative Learning Trilemma: Generative Model Assessment in Data Scarcity Domains. - Marco Salmè; Lorenzo Tronchin; Rosa Sicilia; Paolo Soda; Valerio Guarrasi (CoRR, 2025)