2025 Denoising Score Matching with Random Features: Insights on Diffusion Models from Precise Learning Curves Anand Jerry George, Rodrigo Veiga, and Nicolas Macris 2025 Preprint arXiv PDF Analysis of Diffusion Models for Manifold Data Anand Jerry George, Rodrigo Veiga, and Nicolas Macris 2025 Preprint arXiv PDF 2024 Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features Rodrigo Veiga, Anastasia Remizova, and Nicolas Macris In Proceedings of the 41st International Conference on Machine Learning, 21–27 jul 2024 arXiv HTML PDF 2023 Learning curves for the multi-class teacher–student perceptron Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, and 3 more authors Machine Learning: Science and Technology, Feb 2023 arXiv HTML PDF 2022 Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, and 2 more authors In Advances in Neural Information Processing Systems, Feb 2022 arXiv HTML PDF Restricted Boltzmann Machine Flows and The Critical Temperature of Ising models Rodrigo Veiga, and Renato Vicente Feb 2022 Preprint arXiv PDF 2020 Age-structured estimation of COVID-19 ICU demand from low quality data Rodrigo Veiga, Rodrigo Murta, and Renato Vicente Feb 2020 Preprint arXiv PDF