Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem. - Matteo Giordano; Richard Nickl (CoRR, 2019)

Nonparametric Bayesian inference for reversible multi-dimensional diffusions. - Matteo Giordano; Kolyan Ray (CoRR, 2020)

Bernstein-von Mises Theorems and Uncertainty Quantification for Linear Inverse Problems. - Matteo Giordano; Hanne Kekkonen (SIAM/ASA J. Uncertain. Quantification, 2020)

On the inability of Gaussian process regression to optimally learn compositional functions. - Matteo Giordano; Kolyan Ray; Johannes Schmidt-Hieber (NeurIPS, 2022)

Statistical algorithms for low-frequency diffusion data: A PDE approach. - Matteo Giordano; Sven Wang (CoRR, 2024)

A comparative analysis of machine learning algorithms for predicting probabilities of default. - Adrian Iulian Cristescu; Matteo Giordano (CoRR, 2025)