Flavio Nicoletti | Stef SM Lab

I am Flavio Nicoletti, a postdoc researcher in the Data Science and AI division in the Computer Science department of Chalmers University of Technology and Gothenburg University. Before joining Prof. S. Sarao Mannelli lab, I worked in the years 2020-2023 as a PhD student with Prof. Federico Ricci-Tersenghi (Sapienza University of Rome) and Prof. Silvio Franz (Université Paris-Saclay) in an international cotutelle program, studying the low temperature physics of vector spin glasses. From July 2023 until March 2025, I worked as a Postdoc with Prof. Federico Ricci-Tersenghi, studying generalizations of vector spin glasses to neural network models. My actual research focuses on understanding the impact of bias in Machine Learning and Animal Behaviour, building on simplified and solvable neural networks models.

Contacts and information

Publications

The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models
Flavio Nicoletti, Chenxiao Ma, Enrico Ventura, Luca Saglietti, Stefano Sarao Mannelli
arXiv preprint

Real-world datasets differ across classes in both structure and frequency, but most theory for diffusion models assumes homogeneous data. This work develops a high-dimensional analytical framework for class-dependent learning in score-based diffusion models. Using a random-features model trained on Gaussian mixtures, the paper characterizes how class variance, centroid geometry, and sampling imbalance shape the timing of generalization and memorization. The analysis predicts that diffusion models may memorize some classes while others remain underlearned, and the theory is validated with U-Net experiments on Fashion MNIST. [Read Article]

Contacts and information

Publications

The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models