Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. - Rodrigo Veiga 001; Ludovic Stephan; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2022)

Learning curves for the multi-class teacher-student perceptron. - Elisabetta Cornacchia; Francesca Mignacco; Rodrigo Veiga 001; Cédric Gerbelot; Bruno Loureiro; Lenka Zdeborová (Mach. Learn. Sci. Technol., 2023)

Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features. - Rodrigo Veiga 001; Anastasia Remizova; Nicolas Macris (ICML, 2024)

Denoising Score Matching with Random Features: Insights on Diffusion Models from Precise Learning Curves. - Anand Jerry George; Rodrigo Veiga 001; Nicolas Macris (CoRR, 2025)

Analysis of Diffusion Models for Manifold Data. - Anand Jerry George; Rodrigo Veiga 001; Nicolas Macris (CoRR, 2025)