Author

Marylou Gabrié

3 papers indexed here

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#machine learning Preprint Sep 2026

Weighting Schedules Govern What and When Score-Based Generative Models Learn from Multimodal Data

Score-based generative models generate new samples by integrating a time-dependent drift that carries Gaussian noise onto the target distribution. In practice this drift is modeled by a neural network, trained on a loss integrated over time $t$ with a weighting schedule $w(t)$. Along the backward dynamics, and for mult...

J. Klinger, Raphaël Urfin, Giulio Biroli et al. · 0 citations

#machine learning Preprint Dec 2025

Boltzmann generators for amorphous particle systems

This work develops Boltzmann Generators tailored to amorphous materials by building the required equivariances directly into Riemannian stochastic interpolants and incorporates periodic boundary conditions and particle symmetries using equivariant graph neural networks.

Louis Grenioux, Leonardo Galliano, Ludovic Berthier et al. · 5 citations

#artificial intelligence Preprint May 2026

The critical slowing down in training diffusion models

It is demonstrated that diffusion models can overcome the critical slowing down through appropriate architectural design, and establish a controlled framework for understanding and improving learned sampling methods in statistical physics and beyond.

Luca Maria Del Bono, Giulio Biroli, P. Charbonneau et al. · 1 citation