3 papers
cs.LG2026
Towards More General Control of Diffusion Models Using Jeffrey Guidance
Raphaël Razafindralambo, Rémy Sun, Frédéric Precioso +2
A key strength of diffusion models lies in their flexibility, since their outputs can be controlled at sampling time through guidance. However, beyond simple cases such as conditio…
stat.ML2026
Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means
Raphaël Razafindralambo, Rémy Sun, Frédéric Precioso +2
Density aggregation is a central problem in machine learning, for instance when combining predictions from a Deep Ensemble. The choice of aggregation remains an open question with…
cs.LG2026
When Are Two Scores Better Than One? Investigating Ensembles of Diffusion Models
Raphaël Razafindralambo, Rémy Sun, Frédéric Precioso +2
Diffusion models now generate high-quality, diverse samples, with an increasing focus on more powerful models. Although ensembling is a well-known way to improve supervised models,…