PUBLICATIONS
This page contains only material published in archival journals. For preprints please see the web-pages of the PIs and PDRAs here
2018
S.Agapiou, P.Math茅, Posterior Contraction in Bayesian Inverse Problems Under Gaussian Priors. New Trends in Parameter Identification for Mathematical Models pp 1-29.
S.Agapiou, G.O.Roberts, S.J.Vollmer, Unbiased Monte Carlo: Posterior estimation for intractable/infinite-dimensional models. Bernoulli, 24(3) (2018), 1726-1786.
A.L.Bertozzi, X.Luo, A.M.Stuart, K.C.Zygalakis, Uncertainty Quantification in the Classification of High Dimensional Data. SIAM-ASA JUQ, 6(2) (2018) 568-595.
C.-E. Brehier, M. Hairer and A.M.Stuart, Weak error estimates for trajectories of SPDEs under spectral Galerkin discretization. Journal of Computational Mathematics, 36(2) (2018) 159-182.
D.Calvetti, M.M.Dunlop, E.Somersalo, A.M.Stuart, Iterative Updating of Model Error for Bayesian Inversion. Inverse Problems, 34 (2018) 025008.
N.K.Chada, M.A.Iglesias, L.Roininen, A.M.Stuart, Parameterizations for Ensemble Kalman Inversion. Inverse Problems, 34 (2018) 055009.
A Djurdjevac, CM Elliott, R Kornhuber, T Ranner, Evolving surface finite element methods for random advection-diffusion equations. SIAM/ASA Journal on Uncertainty Quantification, 6(4) (2018) 1656–1684.
J. Kuntz, M. Ottobre, A.M. Stuart, Non-stationary phase of the MALA algorithm. Stochastic PDE: Anal. Comp. (2018).
A.Mendoza, L.Roininen, M.Girolami, J.Heikkinen H.Haario, Statistical Methods To Enable Practical On-Site Tomographic Imaging of Whole-Core Samples. Document IDSPWLA-2018-OOOO, SPWLA 59th Annual Logging Symposium (2018).
C. Schillings and A. Stuart, Convergence analysis of ensemble Kalman inversion: the linear, noisy case, Applicable Analysis 97(1) (2018) 107-123.
A.M.Stuart and A.L.Teckentrup, Posterior consistency for Gaussian process approximations of Bayesian posterior distributions. Mathematics of Computation, 87(310) (2018) 721-753.
2017
S. Agapiou, O. Papaspiliopoulos, D. Sanz-Alonso, A. M. Stuart, Importance sampling: computational complexity and intrinsic dimension. Statistical Science 32(3) (2017), 405-431.
H.Bazargan, M.A.Christie, 'Bayesian Model Selection for Complex Geological Structures Using Polynomial Chaos Proxy' Computational Geosciences (2017).
A.Beskos, M.Girolami, S.Lan, P.E.Farrell, A.M.Stuart, Geometric MCMC for Infinite-Dimensional Inverse Problems. Journal of Computational Physics Volume 335, 15 April 2017, Pages 327-351.
M.Betancourt, S.Byrne, S.Livingstone, M.Girolami (2016) The Geometric Foundations of Hamiltonian Monte Carlo, Bernoulli, 23(4A), 2257 - 2298, 2017. DOI: 10.3150/16-BEJ810.
M.A. Iglesias, K. Lin, S. Lu, A.M. Stuart, Filter based methods for statistical linear inverse problems. Communications in Math. Sciences 15(7) (2017), 1867-1896.
J.J.J.Hutahaean, M.A.Christie, V.Demyanov, On Optimal Selection of Objective Grouping for Multi-Objective History Matching, SPE Journal (2017).
J.J.J.Hutahaean, V.Demyanov, M.A.Christie, Many-objective optimization algorithm applied to history matching. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI), (2017) IEEE. DOI: 10.1109/SSCI.2016.7850215.
W.Lee, A.M.Stuart, Derivation and analysis of simplified filters for complex dynamical systems. Communications in Mathematical Sciences 15(2) (2017), 413-450.
Yulong Lu, Andrew Stuart , and Hendrik Weber, Gaussian Approximations For Transition Paths In Brownian Dynamics. SIAM J. Math. Anal. 49(4) (2017) 3005-3047.
Yulong Lu, Andrew Stuart , and Hendrik Weber, Gaussian Approximations for Probability Measures on Rd. SIAM/ASA J. Uncertainty Quantification 5 (2017) 1136-1165.
C.Oates, M.Girolami, N.Chopin, Control Functionals for Monte Carlo Integration. Journal of Royal Statistical Society - Series B, Volume 79, Issue 3, Pages 695–718, 2017.
D. Sanz-Alonso, A.M. Stuart, Gaussian approximations of small noise diffusions in Kullback-Leibler divergence. Communications in Mathematical Sciences 15(7) (2017), 2087-2097.
C.Schillings and A.M.Stuart, Analysis of the ensemble Kalman filter for inverse problems. SIAM J Numerical Analysis 55(3) (2017), 1264-1290.
R.Scheichl, A.M.Stuart, A.L.Teckentrup, Quasi Monte-Carlo and multi-level Monte Carlo for computing posterior expectations in elliptic inverse problems. SIAM/ASA J. Uncertainty Quantification, 5(1), 493-518, 2017.
T.Schneider, S.Lan, A.Stuart, J.Teixeira, Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations. Geophysical Research Letters 44 (2017).
2016
O.A.Chkrebtii, D.A.Campbell, B.Calderhead, M.A.Girolami. Bayesian Solution Uncertainty Quantification for Differential Equations. Bayesian Analysis, Vol. 11, Number. 4, Pages 1239-1267. with Discussion, 2016.
P.R.Conrad, M.Girolami, S.Sarkka, A.M.Stuart, K.C.Zygalakis, Statistical analysis of differential equations: introducing probability measures on numerical solutions. Statistics and Computing (2016).
P. Conrad, MAG, S.Sarkka, A.M.Stuart, K.Zygalkis. Probability Measures for Numerical Solutions of Differential Equations, Statistics and Computing, 27:1065–1082, 2016.
M.M.Dunlop, M.A.Iglesias, A.M.Stuart, Hierarchical Bayesian level set inversion. Statistics and Computing (2016).
M.M.Dunlop, A.M.Stuart, The Bayesian formulation of EIT: analysis and algorithms. Inverse Problems and Imaging 10(4)(2016) 1007-1036.
M.M.Dunlop, A.M.Stuart, MAP estimators for piecewise continuous inversion. Inverse Problems 32(10) (2016) 105003.
L.Ellam, N.Zabaras, M.Girolami. A Bayesian Approach to Multiscale Inverse Problems with On-the-fly Scale Determination. Journal of Computational Physics, 326, 115-140, 2016.
M.Iglesias, Y.Lu, A.M.Stuart, A Bayesian level set method for geometric inverse problems. Interfaces and Free Boundaries 18 (2016), 181-217.
S.Lan, T.Bui-Thanh, M.Christie, M.Girolami, Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for Bayesian Inverse Problems. Journal of Computational Physics, Volume 308, 1 March 2016, Pages 81-101.
K.J.H.Law, D.Sanz-Alonso, A.Shukla, A.M.Stuart, Filter accuracy for the Lorenz 96 model: fixed versus adaptive observation operators. Physica D: Nonlinear Phenomena 325 (2016) 1-13.
C.Oates, M.Girolami (2016) Control Functionals for Quasi-Monte Carlo Integration. Nineteenth International Conference on Artificial Intelligence and Statistics (AISTATS).
C.Oates, T.Papamarkou, M.Girolami. The Controlled Thermodynamic Integral, Journal of the American Statistical Association, Volume 111, Number 514, 634--645, 2016.
M.Ottobre, N.S.Pillai, F.J.Pinski, A.M.Stuart, A function space HMC algorithm with second order Langevin diffusion limit. Bernoulli 22/1(2016) 60-106.
C. Schillings and C. Schwab. Scaling limits in computational Bayesian inversion, ESAIM: M2AN, 50(6) (2016), 1825-1856.
2015
H.Bazargan, M.A.Christie, A.H.Elsheikh, M.Ahmadi, Surrogate accelerated sampling of reservoir models with complex structures using sparse polynomial chaos expansion, Advances in Water Resources, vol 86, no. Part B (2015) pp. 385–399. DOI: 10.1016/j.advwatres.2015.09.009
A.Beskos, A.Jasra, E.A.Muzaffer, A.M.Stuart, Sequential Monte Carlo methods for Bayesian elliptic inverse problems. Stat. Comp. 25/4 (2015) 727-737.
F.-X.Briol, C.Oates, M.Girolami, M.A.Osborne, (2015). Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees.Advances In Neural Information Processing Systems (NIPS) 2015.
G.Cox, M.A.Christie, Fitting of a Multiphase Equation of State with Swarm Intelligence. Journal of Physics: Condensed Matter. (27) (2015) 405201.
A.B.Duncan, C.M.Elliot, G.A.Pavliotis, A.M.Stuart, A multiscale analysis of diffusions on rapidly varying surfaces. J. Nonlinear Science 25/2 (2015) 389-449.
D.Elsakout, M.Christie, G.Lord, Multilevel Markov Chain Monte Carlo (MLMCMC) For Uncertainty Quantification. SPE North Africa Technical Conference and Exhibition, 14-16 September, Cairo, Egypt. Society of Petroleum Engineers. (2015)
M.Girolami, A.-M.Lynne, H.Strathmann, D.Simpson, Y.Atchade.On Russian Roulette Estimates for Bayesian Inference with Doubly-Intractable Likelihoods Statistical Science, Volume 30, Number 4 (2015), 443-467, 2015.
C.Handley, M.A.Christie, Calibrating reaction rates for the CREST model, Paper presented at 19th Biennial Conference on Shock Compression of Condensed Matter, Tampa, United States, 14/06/15 - 19/06/15 (2015).
P.Hennig, M.A.Osborne, M.Girolami, Probabilistic Numerics and Uncertainty in Computations. Proceedings of the Royal Society A, Proc. R. Soc. A 2015 471 20150142; DOI: 10.1098/rspa.2015.0142.
F.J.Pinski, G.Simpson, A.M.Stuart, H.Weber, Algorithms for Kullback-Leibler approximation for probability measures in infinite dimensions. SIAM J. Sci. Comp. 37/6 (2015) A2733–A2757.
F.J.Pinski, G.Simpson, A.M.Stuart, H.Weber, Kullback-Leibler approximation for probability measures on infinite dimensional spaces. SIAM J. Mathematical Analysis 47(2015) 4091-4122.
S.Reich, A.M.Stuart. Data Assimilation: New Challenges in Random and Stochastic Dynamical Systems. SIAM News, October and November 2015.
D.Sanz-Alonso, A.M.Stuart, Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems. SIAM/ASA J. Uncertainty Quantification, 3(1) (2015) 1200-1220.
C.Schillings, M.Sunn氓ker, J.Stelling, Ch.Schwab, Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks, PLOS Comp. Biol., 2015.
2014
S.Agapiou, J.M.Bardsley, O.Papaspiliopoulos, A.M.Stuart, Analysis of the Gibbs sampler for hierarchical inverse problems. SIAM JUQ, 2 (2014) 514-544.
S.Agapiou, A.M.Stuart, Y-X.Zhang, Bayesian posterior contraction rates for linear severely ill-posed inverse problems. Journal of Inverse and Ill-Posed Problems, 22(2014), 297-321.
T.Bui, M.Girolami, Solving Large-Scale PDE-constrained Bayesian Inverse problems with Riemann Manifold Hamiltonian Monte Carlo. Inverse Problems, 30 (2014) 114014.
M.Filiponne, M.Girolami, Pseudo-Marginal Bayesian Inference for Gaussian Processes. IEEE Transactions Pattern Analysis and Machine Intelligence, 36(11) (2014) 2214-2226.
M.Hairer, A.M.Stuart, S.J.Vollmer, Spectral Gaps for a Metropolis–Hastings Algorithm in Infinite Dimensions. The Annals of Applied Probability, 24/6(2014), 2455-2490.
V.H.Hoang, K.J.H.Law, A.M.Stuart, Determining white noise forcing from Eulerian observations in the Navier-Stokes equation. Stochastic PDEs: Analysis and Computation, 2(2014), 233-261.
M.A.Iglesias, K.Lin, A.M.Stuart, Well-posed Bayesian geometric inverse problems arising in subsurface flow. Inverse Problems, 30 (2014) 114001.
M.Iglesias, A.M.Stuart. Inverse Problems and Uncerrainty Quantification. SIAM News, July/August 2014.
D.T.B.Kelly, K.J.H.Law, A.M.Stuart, Well-posedness and accuracy of the ensemble Kalman filter In discrete and continuous time. Nonlinearity, 27 (2014) 2579-2603.
K.J.H.Law, A.Shukla, A.M.Stuart, Analysis of the 3DVAR Filter for the Partially Observed Lorenz '63 Model. Discrete and Continuous Dynamical Systems A, 34(2014), 1061-1078.
N.S.Pillai, A.M.Stuart, A.H. Thiery, Noisy gradient flow from a random walk in Hilbert space. Stochastic PDEs: Analysis and Computation, 2(2014), 196-232.
2013
S.Agapiou, S.Larsson, A.M. Stuart, Posterior consistency of the Bayesian approach to linear ill-posed inverse problems. Stochastic Processes and Applications, 123/10 (2013) 3828-3860.
A.Beskos, N.Pillai, G.Roberts, J.-M.Sanz-Serna, A.M.Stuart, Optimal tuning of the hybrid Monte Carlo algorithm. Bernoulli 19(2013), 1501-1534.
D.Bloemker, K.J.H.Law, A.M.Stuart, K.Zygalalkis, Accuracy and stability of the continuous-time 3DVAR filter for the Navier-Stokes equation. Nonlinearity 26(2013), 2193-2219.
C.E.A.Brett, K.F.Lam, K.J.H.Law, D.S.McCormick, M.R.Scott, A.M.Stuart, Accuracy and stability of filters for dissipative PDEs. Physica D 245 (2013) 34-45
S.L.Cotter, G.O.Roberts, A.M.Stuart, D. White, MCMC methods for functions: modifying old algorithms to make them faster. Statistical Science, 28 (2013) 424-446).
M.Dashti, K.J.H.Law, A.M.Stuart, J.Voss, MAP estimators and posterior consistency in Bayesian nonparametric inverse problems. Inverse Problems, 29(2013) 095017.
V.H.Hoang, C.Schwab, A.M.Stuart, Complexity analysis of accelerated MCMC methods for Bayesian inversion. Inverse Problems, 29/8 (2013) 085010
M.A.Iglesias, K.J.H.Law, A.M.Stuart, Evaluation of Gaussian approximations for data assimilation in reservoir models. Computational Geosciences. 17(2013), 851-885.
M.A.Iglesias, K.J.H.Law, A.M.Stuart, Ensemble Kalman Methods for Inverse Problems. Inverse Problems, 29(2013) 045001.
Y.Pokern, A.M.Stuart, J.H.Van Zanten, Posterior consistency via precision operators for nonparametric drift estimation in SDEs. Stochastic Processes and Their Applications, 123/2 (2013) 603-628.