Hierarchical Bayesian level set inversion. - Matthew M. Dunlop; Marco A. Iglesias; Andrew M. Stuart (Stat. Comput., 2017)

Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms. - Matthew M. Dunlop; Dejan Slepcev; Andrew M. Stuart; Matthew Thorpe (CoRR, 2018)

How Deep Are Deep Gaussian Processes? - Matthew M. Dunlop; Mark A. Girolami; Andrew M. Stuart; Aretha L. Teckentrup (J. Mach. Learn. Res., 2018)

Reconciling Bayesian and Perimeter Regularization for Binary Inversion. - Oliver R. A. Dunbar; Matthew M. Dunlop; Charles M. Elliott; Viet Ha Hoang; Andrew M. Stuart (SIAM J. Sci. Comput., 2020)

Bayesian neural network priors for edge-preserving inversion. - Chen Li 003; Matthew M. Dunlop; Georg Stadler (CoRR, 2021)

Stability of Gibbs Posteriors from the Wasserstein Loss for Bayesian Full Waveform Inversion. - Matthew M. Dunlop; Yunan Yang (SIAM/ASA J. Uncertain. Quantification, 2021)

A gradient-free subspace-adjusting ensemble sampler for infinite-dimensional Bayesian inverse problems. - Matthew M. Dunlop; Georg Stadler (CoRR, 2022)