Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data. - Umberto M. Tomasini; Antonio Sclocchi; Matthieu Wyart (ICML, 2022)

Failure and success of the spectral bias prediction for Kernel Ridge Regression: the case of low-dimensional data. - Umberto M. Tomasini; Antonio Sclocchi; Matthieu Wyart (CoRR, 2022)

Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning. - Antonio Sclocchi; Mario Geiger; Matthieu Wyart (ICML, 2023)

On the different regimes of Stochastic Gradient Descent. - Antonio Sclocchi; Matthieu Wyart (CoRR, 2023)

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

Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants. - Beatriz Borges; Negar Foroutan; Deniz Bayazit; Anna Sotnikova; Syrielle Montariol; Tanya Nazaretzky; Mohammadreza Banaei; Alireza Sakhaeirad; Philippe Servant; Seyed Parsa Neshaei; Jibril Frej; Angelika Romanou; et al. (CoRR, 2024)

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