Locality defeats the curse of dimensionality in convolutional teacher-student scenarios. - Alessandro Favero; Francesco Cagnetta; Matthieu Wyart (NeurIPS, 2021)

Relative stability toward diffeomorphisms indicates performance in deep nets. - Leonardo Petrini; Alessandro Favero; Mario Geiger; Matthieu Wyart (NeurIPS, 2021)

Relative stability toward diffeomorphisms in deep nets indicates performance. - Leonardo Petrini; Alessandro Favero; Mario Geiger; Matthieu Wyart (CoRR, 2021)

How Wide Convolutional Neural Networks Learn Hierarchical Tasks. - Francesco Cagnetta; Alessandro Favero; Matthieu Wyart (CoRR, 2022)

What Can Be Learnt With Wide Convolutional Neural Networks? - Francesco Cagnetta; Alessandro Favero; Matthieu Wyart (ICML, 2023)

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models. - Guillermo Ortiz-Jiménez; Alessandro Favero; Pascal Frossard (NeurIPS, 2023)

How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model. - Leonardo Petrini; Francesco Cagnetta; Umberto M. Tomasini; Alessandro Favero; Matthieu Wyart (CoRR, 2023)

Multi-Modal Hallucination Control by Visual Information Grounding. - Alessandro Favero; Luca Zancato; Matthew Trager; Siddharth Choudhary; Pramuditha Perera; Alessandro Achille; Ashwin Swaminathan; Stefano Soatto (CVPR, 2024)

A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data. - Antonio Sclocchi; Alessandro Favero; Matthieu Wyart (CoRR, 2024)

Probing the Latent Hierarchical Structure of Data via Diffusion Models. - Antonio Sclocchi; Alessandro Favero; Noam Itzhak Levi; Matthieu Wyart (ICLR, 2025)

LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging. - Ke Wang; Nikolaos Dimitriadis; Alessandro Favero; Guillermo Ortiz-Jiménez; François Fleuret; Pascal Frossard (ICLR, 2025)

How compositional generalization and creativity improve as diffusion models are trained. - Alessandro Favero; Antonio Sclocchi; Francesco Cagnetta; Pascal Frossard; Matthieu Wyart (CoRR, 2025)

Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures. - Francesco Cagnetta; Alessandro Favero; Antonio Sclocchi; Matthieu Wyart (CoRR, 2025)

Bigger Isn't Always Memorizing: Early Stopping Overparameterized Diffusion Models. - Alessandro Favero; Antonio Sclocchi; Matthieu Wyart (CoRR, 2025)

MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs. - Ke Wang; Yiming Qin; Nikolaos Dimitriadis; Alessandro Favero; Pascal Frossard (CoRR, 2025)