| Feb 1, 2025 | Diffusion models have become the state-of-the-art for generative modeling in images, but there’s still much to uncover about their theoretical foundations. In collaboration with Anand Jerry George and Nicolas Macris, we dive into these aspects in our two latest preprints. In Denoising Score Matching with Random Features: Insights on Diffusion Models from Precise Learning Curves, we analyse the time-reversed dynamics of denoising score matching in generative diffusion models, leveraging random feature neural networks to derive precise learning curves. In Analysis of Diffusion Models for Manifold Data, explore the behaviour of diffusion models when data lies on a manifold, under the assumption of an exact empirical score. |
| Jul 23, 2024 | Together with my colleague Anastasia Remizova, I will be presenting our work Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features on the Poster Session 1 at ICML, Hall C 4-9, from 11:30 am to 1 pm (CEST). We will be next to poster #1901. Come and have a chat with us! |
| May 20, 2024 | It was a pleasure to visit ICTP in Trieste, Italy, to attend and give a talk at the Youth in High Dimensions: Recent Progress in Machine Learning, High-Dimensional Statistics and Inference conference. |
| May 2, 2024 | Our paper Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features, in collaboration with Anastasia Remizova and Nicolas Macris, has been accepted to ICML 2024. See you in Vienna in July! |
| Apr 15, 2024 | This week, I have the pleasure of attending and giving a talk at the From Theory to Practice workshop at the AIMS Research and Innovation Centre in Kigali, Rwanda. |