collaborators

5 papers

math.NA2026

Dimension-Free Multimodal Sampling via Preconditioned Annealed Langevin Dynamics

Lorenzo Baldassari, Josselin Garnier, Knut Solna +1

Designing sampling algorithms for multimodal targets that remain stable under refinement of the finite-dimensional approximation of an underlying function-space problem is a centra…

stat.ML2026

Dimension-Uniform Discretization Analysis of Preconditioned Annealed Langevin Dynamics for Multimodal Gaussian Mixtures

Lorenzo Baldassari, Josselin Garnier, Knut Solna +1

Obtaining stable diffusion-based samplers in high- and infinite-dimensional settings is challenging because errors can accumulate across high-frequency coordinates and make the dyn…

eess.IV2026

Gaussian Surrogates for Poisson Imaging: Some Theoretical and Empirical Results

Alexandra Spitzer, Lorenzo Baldassari, Valentin Derbanot +1

In imaging inverse problems with Poisson-distributed measurements, it is common to use objectives derived from the Poisson likelihood. But performance is often evaluated by mean sq…

math.ST2026

On Observation Time for Recovering Latent Hawkes Networks

Jonas Linkerhägner, Michele Bortolasi, Lorenzo Baldassari +2

Dynamics of interacting systems in engineering, society, and nature often evolve over latent networks that govern which entities can interact. We study the problem of inferring the…

stat.ML2025

Preconditioned Langevin Dynamics with Score-Based Generative Models for Infinite-Dimensional Linear Bayesian Inverse Problems

Lorenzo Baldassari, Josselin Garnier, Knut Solna +1

Designing algorithms for solving high-dimensional Bayesian inverse problems directly in infinite-dimensional function spaces - where such problems are naturally formulated - is cru…