Maarten V. de Hoop

Transformers through the lens of support-preserving maps between measures

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

Transformers are Universal In-context Learners

Semialgebraic Neural Networks: From roots to representations

Theoretical Convergence Analysis for Hilbert Space MCMC with Score-based Priors for Nonlinear Bayesian Inverse Problems