| How deep are deep Gaussian processes? MM Dunlop, MA Girolami, AM Stuart, AL Teckentrup Journal of Machine Learning Research 19 (54), 1-46, 2018 | 144 | 2018 |
| Hierarchical Bayesian level set inversion MM Dunlop, MA Iglesias, AM Stuart Statistics and Computing 27, 1555-1584, 2017 | 111 | 2017 |
| The Bayesian formulation of EIT: analysis and algorithms MM Dunlop, AM Stuart Inverse Problems & Imaging 10 (4), 1007-1036, 2015 | 71 | 2015 |
| Iterative updating of model error for Bayesian inversion D Calvetti, M Dunlop, E Somersalo, A Stuart Inverse Problems 34 (2), 025008, 2018 | 59 | 2018 |
| Large data and zero noise limits of graph-based semi-supervised learning algorithms MM Dunlop, D Slepčev, AM Stuart, M Thorpe Applied and Computational Harmonic Analysis 49 (2), 655-697, 2020 | 56 | 2020 |
| Dimension-robust MCMC in Bayesian inverse problems V Chen, MM Dunlop, O Papaspiliopoulos, AM Stuart arXiv preprint arXiv:1803.03344, 2018 | 48* | 2018 |
| MAP estimators for piecewise continuous inversion MM Dunlop, AM Stuart Inverse Problems 32 (10), 105003, 2016 | 23 | 2016 |
| Hyperparameter estimation in Bayesian MAP estimation: parameterizations and consistency MM Dunlop, T Helin, AM Stuart The SMAI journal of computational mathematics 6, 69-100, 2020 | 15 | 2020 |
| Stability of Gibbs posteriors from the Wasserstein loss for Bayesian full waveform inversion MM Dunlop, Y Yang SIAM/ASA Journal on Uncertainty Quantification 9 (4), 1499-1526, 2021 | 13 | 2021 |
| Multiplicative noise in Bayesian inverse problems: Well-posedness and consistency of MAP estimators MM Dunlop arXiv preprint arXiv:1910.14632, 2019 | 11 | 2019 |
| Bayesian neural network priors for edge-preserving inversion C Li, M Dunlop, G Stadler arXiv preprint arXiv:2112.10663, 2021 | 10 | 2021 |
| Large data and zero noise limits of graph-based semi-supervised learning algorithms MM Dunlop, D Slepčev, AM Stuart, M Thorpe arXiv preprint arXiv:1805.09450, 2018 | 9 | 2018 |
| A gradient-free subspace-adjusting ensemble sampler for infinite-dimensional Bayesian inverse problems MM Dunlop, G Stadler arXiv preprint arXiv:2202.11088, 2022 | 6 | 2022 |
| Reconciling Bayesian and perimeter regularization for binary inversion ORA Dunbar, MM Dunlop, CM Elliott, VH Hoang, AM Stuart arXiv, 2020 | 6* | 2020 |
| Analysis and computation for Bayesian inverse problems MM Dunlop University of Warwick, 2016 | 4 | 2016 |
| New likelihood functions and level-set prior for Bayesian full-waveform inversion M Dunlop, Y Yang SEG Technical Program Expanded Abstracts 2020, 825-829, 2020 | 1 | 2020 |
| RECONCILING BAYESIAN AND TOTAL VARIATION REGULARIZATION METHODS FOR BINARY INVERSION MM DUNLOP, CM ELLIOTT, VHA HOANG, AM STUART arXiv preprint arXiv:1706.01960, 2017 | | 2017 |
| Hierarchical Bayesian Level Set Inversion: Supplementary Figures MM Dunlop, MA Iglesias, AM Stuart | | |
Andrew M StuartComputing + Mathematical Sciences, Caltechכתובת אימייל מאומתת בדומיין caltech.edu
