Schneider, Tapio; Stuart, Andrew M. et al. (2022) Ensemble Kalman inversion for sparse learning of dynamical systems from time-averaged data Journal of Computational Physics; Vol. 470;
Dunbar, Oliver R. A.; Howland, Michael F. et al. (2022) Ensemble-Based Experimental Design for Targeting Data Acquisition to Inform Climate Models Journal of Advances in Modeling Earth Systems; Vol. 14; No. 9;
Huang, Daniel Zhengyu; Schneider, Tapio et al. (2022) Iterated Kalman methodology for inverse problems Journal of Computational Physics; Vol. 463;
Liu, Ziming; Stuart, Andrew M. et al. (2022) Second Order Ensemble Langevin Method for Sampling and Inverse Problems arXiv;
Dunbar, Oliver R. A.; Duncan, Andrew B. et al. (2022) Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods SIAM Journal on Applied Dynamical Systems; Vol. 21; No. 2;
Carrillo, J. A.; Hoffmann, F. et al. (2022) Consensus-based sampling Studies in Applied Mathematics; Vol. 148; No. 3;
Kovachki, Nikola; Liu, Burigede et al. (2022) Multiscale modeling of materials: Computing, data science, uncertainty and goal-oriented optimization Mechanics of Materials; Vol. 165;
Pavliotis, G. A.; Stuart, A. M. et al. (2022) Derivative-Free Bayesian Inversion Using Multiscale Dynamics SIAM Journal on Applied Dynamical Systems; Vol. 21; No. 1;
Dunbar, Oliver R. A.; Howland, Michael F. et al. (2022) Ensemble-Based Experimental Design for Targeted High-Resolution Simulations to Inform Climate Models
Liu, Burigede; Kovachki, Nikola et al. (2022) A learning-based multiscale method and its application to inelastic impact problems Journal of the Mechanics and Physics of Solids; Vol. 158;
Hoffmann, Franca; Hosseini, Bamdad et al. (2022) Spectral analysis of weighted Laplacians arising in data clustering Applied and Computational Harmonic Analysis; Vol. 56;
Chen, Yifan; Hosseini, Bamdad et al. (2021) Solving and learning nonlinear PDEs with Gaussian processes Journal of Computational Physics; Vol. 447;
Abdulle, Assyr; Garegnani, Giacomo et al. (2021) Drift Estimation of Multiscale Diffusions Based on Filtered Data Foundations of Computational Mathematics; (In Press)
Bertozzi, Andrea L.; Hosseini, Bamdad et al. (2021) Posterior consistency of semi-supervised regression on graphs Inverse Problems; Vol. 37; No. 10;
Nelsen, Nicholas H.; Stuart, Andrew M. (2021) The Random Feature Model for Input-Output Maps between Banach Spaces SIAM Journal on Scientific Computing; Vol. 43; No. 5;
Dunbar, Oliver R. A.; Garbuno-Inigo, Alfredo et al. (2021) Calibration and Uncertainty Quantification of Convective Parameters in an Idealized GCM Journal of Advances in Modelling Earth Systems; Vol. 13; No. 9;
de Hoop, Maarten V.; Kovachki, Nikola B. et al. (2021) Convergence Rates for Learning Linear Operators from Noisy Data arXiv;
Kovachki, Nikola; Li, Zongyi et al. (2021) Neural Operator: Learning Maps Between Function Spaces arXiv;
Levine, Matthew E.; Stuart, Andrew M. (2021) A Framework for Machine Learning of Model Error in Dynamical Systems arXiv;
Burov, Dmitry; Giannakis, Dimitrios et al. (2021) Kernel Analog Forecasting: Multiscale Test Problems Multiscale Modeling and Simulation; Vol. 19; No. 2;
Chen, Yifang; Owhadi, Houman et al. (2021) Consistency of empirical Bayes and kernel flow for hierarchical parameter estimation Mathematics of Computation; Vol. 90;
Li, Zongyi; Kovachki, Nikola et al. (2021) Learning Dissipative Dynamics in Chaotic Systems arXiv;
Cleary, Emmet; Garbuno-Inigo, Alfredo et al. (2021) Calibrate, emulate, sample Journal of Computational Physics; Vol. 424;
Kovachki, Nikola B.; Stuart, Andrew M. (2021) Continuous Time Analysis of Momentum Methods Journal of Machine Learning Research; Vol. 22; No. 17;
Li, Zongyi; Kovachki, Nikola et al. (2020) Multipole Graph Neural Operator for Parametric Partial Differential Equations Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020); arXiv; 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020 , [Online Only]
Li, Zongyi; Kovachki, Nikola et al. (2020) Fourier Neural Operator for Parametric Partial Differential Equations arXiv;
Dunlop, Matthew M.; Slepčev, Dejan et al. (2020) Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms Applied and Computational Harmonic Analysis; Vol. 49; No. 2;
Schneider, Tapio; Stuart, Andrew M. et al. (2020) Ensemble Kalman Inversion for Sparse Learning of Dynamical Systems from Time-Averaged Data arXiv;
Dunbar, Oliver R. A.; Dunlop, Matthew M. et al. (2020) Reconciling Bayesian and Perimeter Regularization for Binary Inversion SIAM Journal on Scientific Computing; Vol. 42; No. 4;
Hoffmann, Franca; Hosseini, Bamdad et al. (2020) Consistency of Semi-Supervised Learning Algorithms on Graphs: Probit and One-Hot Methods Journal of Machine Learning Research; Vol. 21;
Seylabi, Elnaz; Stuart, Andrew M. et al. (2020) Site Characterization at Downhole Arrays by Joint Inversion of Dispersion Data and Acceleration Time Series Bulletin of the Seismological Society of America; Vol. 110; No. 3;
Bhattacharya, Kaushik; Hosseini, Bamdad et al. (2020) Model Reduction and Neural Networks for Parametric PDEs arXiv;
Newton, Kit; Li, Qin et al. (2020) Diffusive optical tomography in the Bayesian framework Multiscale Modeling and Simulation; Vol. 18; No. 2;
Chada, Neil K.; Stuart, Andrew M. et al. (2020) Tikhonov Regularization Within Ensemble Kalman Inversion SIAM Journal on Numerical Analysis; Vol. 58; No. 2;
Schneider, Tapio; Stuart, Andrew M. et al. (2020) Learning Stochastic Closures Using Ensemble Kalman Inversion arXiv;
Li, Zongyi; Kovachki, Nikola et al. (2020) Neural Operator: Graph Kernel Network for Partial Differential Equations arXiv;
Stuart, Andrew M.; Wolfram, Marie-Therese (2020) Inverse optimal transport SIAM Journal on Applied Mathematics; Vol. 80; No. 1;
Garbuno-Inigo, Alfredo; Hoffmann, Franca et al. (2020) Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler SIAM Journal on Applied Dynamical Systems; Vol. 19; No. 1;
Lie, Han Cheng; Stuart, A. M. et al. (2019) Strong convergence rates of probabilistic integrators for ordinary differential equations Statistics and Computing; Vol. 29; No. 6;
Albers, D. J.; Levine, M. E. et al. (2019) A Simple Modeling Framework For Prediction In The Human Glucose-Insulin System arXiv;
Kuntz, Juan; Ottobre, Michela et al. (2019) Diffusion Limit For The Random Walk Metropolis Algorithm Out Of stationarity Annales De l'Institut Henri Poincaré - Probabilitiés et Statistiques; Vol. 55; No. 3;
Kovachki, Nikola B.; Stuart, Andrew M. (2019) Ensemble Kalman Inversion: A Derivative-Free Technique For Machine Learning Tasks Inverse Problems; Vol. 35; No. 9;
Albers, David J.; Blancquart, Paul-Adrien et al. (2019) Ensemble Kalman Methods With Constraints Inverse Problems; Vol. 35; No. 9;
Kelly, David; Stuart, Andrew M. (2019) Ergodicity and Accuracy of Optimal Particle Filters for Bayesian Data Assimilation Chinese Annals of Mathematics, Series B; Vol. 40; No. 5;
Gomes, Susana N.; Stuart, Andrew M. et al. (2019) Parameter estimation for macroscopic pedestrian dynamics models from microscopic data SIAM Journal on Applied Mathematics; Vol. 79; No. 4;
Kovachki, Nikola B.; Stuart, Andrew M. (2019) Analysis Of Momentum Methods arXiv;
Dunlop, Matthew M.; Helin, Tapio et al. (2019) Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency arXiv;
Qiao, Yiling; Shi, Chang et al. (2019) Uncertainty quantification for semi-supervised multi-class classification in image processing and ego-motion analysis of body-worn videos Electronic Imaging; Vol. 2019; IS&T International Symposium on Electronic Imaging 2019: Image Processing: Algorithms and Systems XVII, 13-17 January 2019 , Burlingame, CA
Stuart, Andrew; Taeb, Armeen (2018) Data Assimilation and Inverse Problems arXiv;
Albers, David J.; Levine, Matthew E. et al. (2018) Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype Journal of the American Medical Informatics Association; Vol. 25; No. 10;
Dunlop, Matthew M.; Girolami, Mark A. et al. (2018) How Deep Are Deep Gaussian Processes? Journal of Machine Learning Research; Vol. 19; No. 54;
Kuntz, Juan; Ottobre, Michela et al. (2018) Non-stationary phase of the MALA algorithm Stochastics and Partial Differential Equations: Analysis and Computations; Vol. 6; No. 3;
Chada, Neil K.; Iglesias, Marco A. et al. (2018) Parameterizations for ensemble Kalman inversion Inverse Problems; Vol. 34; No. 5;
Bertozzi, Andrea L.; Luo, Xiyang et al. (2018) Uncertainty Quantification in Graph-Based Classification of High Dimensional Data SIAM/ASA Journal on Uncertainty Quantification; Vol. 6; No. 2;
Bréhier, Charles-Edouard; Hairer, Martin et al. (2018) Weak error estimates for trajectories of SPDEs for Spectral Galerkin discretization Journal of Computational Mathematics; Vol. 36; No. 2;
Chen, Victor; Dunlop, Matthew M. et al. (2018) Dimension-Robust MCMC in Bayesian Inverse Problems arXiv;
Stuart, Andrew M.; Teckentrup, Aretha L. (2018) Posterior consistency for Gaussian process approximations of Bayesian posterior distributions Mathematics of Computation; Vol. 87; No. 310;
Calvetti, Daniela; Dunlop, Matthew et al. (2018) Iterative Updating of Model Error for Bayesian Inversion Inverse Problems; Vol. 34; No. 2;
Schillings, C.; Stuart, A. M. (2018) Convergence analysis of ensemble Kalman inversion: the linear, noisy case Applicable Analysis: An International Journal; Vol. 97; No. 1;
Schneider, Tapio; Lan, Shiwei et al. (2017) Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations Geophysical Research Letters; Vol. 44; No. 24;
Lu, Yulong; Stuart, Andrew et al. (2017) Gaussian Approximations for Probability Measures on R^d SIAM/ASA Journal on Uncertainty Quantification; Vol. 5; No. 1;
Dunlop, Matthew M.; Iglesias, Marco A. et al. (2017) Hierarchical Bayesian level set inversion Statistics and Computing; Vol. 27; No. 6;
Sanz-Alonso, Daniel; Stuart, Andrew M. (2017) Gaussian Approximations of Small Noise Diffusions in Kullback-Leibler Divergence Communications in Mathematical Sciences; Vol. 15; No. 7;
Agapiou, S.; Papaspiliopoulos, O. et al. (2017) Importance Sampling: Intrinsic Dimension and Computational Cost Statistical Science; Vol. 32; No. 3;
Lu, Yulong; Stuart, Andrew et al. (2017) Gaussian Approximations for Transition Paths in Brownian Dynamics SIAM Journal on Mathematical Analysis; Vol. 49; No. 4;
Conrad, Patrick R.; Girolami, Mark et al. (2017) Statistical analysis of differential equations: introducing probability measures on numerical solutions Statistics and Computing; Vol. 27; No. 4;
Dunlop, Matthew M.; Elliott, Charles M. et al. (2017) Reconciling Bayesian and Total Variation Methods for Binary Inversion arXiv;
Schillings, Claudia; Stuart, Andrew M. (2017) Analysis of the ensemble Kalman filter for inverse problems SIAM Journal on Numerical Analysis; Vol. 55; No. 3;
Scheichl, R.; Stuart, A. M. et al. (2017) Quasi-Monte Carlo and Multilevel Monte Carlo Methods for Computing Posterior Expectations in Elliptic Inverse Problems SIAM/ASA Journal on Uncertainty Quantification; Vol. 5; No. 1;
Beskos, Alexandros; Girolami, Mark et al. (2017) Geometric MCMC for Infinite-Dimensional Inverse Problems Journal of Computational Physics; Vol. 335;
Schillings, C.; Stuart, A. M. (2017) Convergence Analysis of the Ensemble Kalman Filter for Inverse Problems: the Noisy Case (Submitted)
Lee, Wongjung; Stuart, Andrew (2017) Derivation and analysis of simplified filters Communications in Mathematical Sciences; Vol. 15; No. 2;
Iglesias, Marco A.; Lin, Kui et al. (2017) Filter Based Methods For Statistical Linear Inverse Problems Communications in Mathematical Sciences; Vol. 15; No. 7;
Dashti, Masoumeh; Stuart, Andrew M. (2017) The Bayesian Approach to Inverse Problems Handbook of Uncertainty Quantification;
Dunlop, Matthew M.; Stuart, Andrew M. (2016) The Bayesian formulation of EIT: Analysis and algorithms Inverse Problems and Imaging; Vol. 10; No. 4;
Dunlop, M. M.; Stuart, A. M. (2016) MAP estimators for piecewise continuous inversion Inverse Problems; Vol. 32; No. 10;
Law, K. J. H.; Sanz-Alonso, D. et al. (2016) Filter accuracy for the Lorenz 96 model: fixed versus adaptive observation operators Physica D: Nonlinear Phenomena; Vol. 325;
Bühlmann, Peter; Stuart, A. M. (2016) Mathematics, Statistics and Data Science EMS Newsletter; EMS Newsletter; Vol. 100;
Lu, Yulong; Stuart, Andrew M. et al. (2016) Gaussian approximations for transition paths in molecular dynamics (Submitted)
Ottobre, Michela; Pillai, Natesh S. et al. (2016) A Function Space HMC Algorithm With Second Order Langevin Diffusion Limit Bernoulli; Vol. 22; No. 1;
Iglesias, Marco A.; Lu, Yulong et al. (2016) A Bayesian Level Set Method for Geometric Inverse Problems Interfaces and Free Boundaries; Vol. 18; No. 2;
Sanz-Alonso, Daniel; Stuart, Andrew M. (2015) Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems SIAM/ASA Journal on Uncertainty Quantification; Vol. 3; No. 1;
Beskos, Alexandros; Jasra, Ajay et al. (2015) Sequential Monte Carlo methods for Bayesian elliptic inverse problems Statistics and Computing; Vol. 25; No. 4;
Duncan, A. B.; Elliott, C. M. et al. (2015) A Multiscale Analysis of Diffusions on Rapidly Varying Surfaces Journal of Nonlinear Science; Vol. 25; No. 2;
Pinski, F. J.; Simpson, G. et al. (2015) Algorithms for Kullback--Leibler Approximation of Probability Measures in Infinite Dimensions SIAM Journal on Scientific Computing; Vol. 37; No. 6;
Law, Kody; Stuart, Andrew et al. (2015) Data Assimilation: A Mathematical Introduction Vol. 62; Series.Texts in Applied Mathematics;
Reich, Sebastian; Stuart, Andrew M. (2015) Data Assimilation: New Challenges in Random and Stochastic Dynamical Systems SIAM News; SIAM News; Vol. 48; No. 8 & 9; 2015 SIAM Conference on Applications of Dynamical Systems, May 17-21, 2015 , Snowbird, UT
Pinski, F. J.; Simpson, G. et al. (2015) Kullback-Leibler approximation for probability measures on infinite dimensional spaces SIAM Journal on Mathematical Analysis; Vol. 47; No. 6;
Hairer, Martin; Stuart, Andrew M. et al. (2014) Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions Annals of Applied Probability; Vol. 24; No. 6;
Iglesias, Marco A.; Lin, Kui et al. (2014) Well-posed Bayesian geometric inverse problems arising in subsurface flow Inverse Problems; Vol. 30; No. 11;
Kelly, D. B. T.; Law, K. J. H. et al. (2014) Well-posedness and accuracy of the ensemble Kalman filter in discrete and continuous time Nonlinearity; Vol. 27; No. 10;
Agapiou, Sergios; Bardsley, Jonathan M. et al. (2014) Analysis of the Gibbs Sampler for Hierarchical Inverse Problems SIAM/ASA Journal on Uncertainty Quantification; Vol. 2; No. 1;
Agapiou, Sergios; Stuart, Andrew M. et al. (2014) Bayesian posterior contraction rates for linear severely ill-posed inverse problems Journal of Inverse and Ill-posed Problems; Vol. 22; No. 3;
Hoang, Viet Ha; Law, Kody J. H. et al. (2014) Determining white noise forcing from Eulerian observations in the Navier-Stokes equation Stochastic Partial Differential Equations: Analysis and Computations; Vol. 2; No. 2;
Pillai, Natesh S.; Stuart, Andrew M. et al. (2014) Noisy gradient flow from a random walk in Hilbert space Stochastic Partial Differential Equations: Analysis and Computations; Vol. 2; No. 2;
Law, Kody; Shukla, Abishek et al. (2014) Analysis of the 3DVAR filter for the partially observed Lorenz'63 model Discrete and Continuous Dynamical Systems A; Vol. 34; No. 3;
Iglesias, Marco; Stuart, Andrew M. (2014) Inverse Problems and Uncertainty Quantification SIAM News; SIAM News; 2014 SIAM Conference on Uncertainty Quantification, March 31-April 3, 2014 , Savannah, GA
Beskos, Alexandros; Pillai, Natesh et al. (2013) Optimal tuning of the hybrid Monte Carlo algorithm Bernoulli; Vol. 19; No. 5A;
Agapiou, Sergios; Larsson, Stig et al. (2013) Posterior contraction rates for the Bayesian approach to linear ill-posed inverse problems Stochastic Processes and their Applications; Vol. 123; No. 10;
Dashti, M.; Law, K. J. H. et al. (2013) MAP estimators and their consistency in Bayesian nonparametric inverse problems Inverse Problems; Vol. 29; No. 9;
Cotter, S. L.; Roberts, G. O. et al. (2013) MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster Statistical Science; Vol. 28; No. 3;
Hoang, Viet Ha; Schwab, Christoph et al. (2013) Complexity analysis of accelerated MCMC methods for Bayesian inversion Inverse Problems; Vol. 29; No. 8;
Blömker, D.; Law, K. et al. (2013) Accuracy and stability of the continuous-time 3DVAR filter for the Navier–Stokes equation Nonlinearity; Vol. 26; No. 8;
Iglesias, Marco A.; Law, Kody et al. (2013) Evaluation of Gaussian approximations for data assimilation in reservoir models Computational Geosciences; Vol. 17; No. 5;
Iglesias, Marco A.; Law, Kody J. H. et al. (2013) Ensemble Kalman methods for inverse problems Inverse Problems; Vol. 29; No. 4;
Brett, C. E. A.; Lam, K. F. et al. (2013) Accuracy and stability of filters for dissipative PDEs Physica D: Nonlinear Phenomena; Vol. 245; No. 1;
Pokern, Y.; Stuart, A. M. et al. (2013) Posterior consistency via precision operators for Bayesian nonparametric drift estimation in SDEs Stochastic Processes and their Applications; Vol. 123; No. 2;
Pillai, Natesh S.; Stuart, Andrew M. et al. (2012) Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions Annals of Applied Probability; Vol. 22; No. 6;
Law, K. J. H.; Stuart, A. M. (2012) Evaluating Data Assimilation Algorithms Monthly Weather Review; Vol. 140;
Papaspiliopoulos, Omiros; Pokern, Yvo et al. (2012) Nonparametric estimation of diffusions: a differential equations approach Biometrika; Vol. 99; No. 3;
Mattingly, Jonathan C.; Pillai, Natesh S. et al. (2012) Diffusion limits of the random walk Metropolis algorithm in high dimensions Annals of Applied Probability; Vol. 22; No. 3;
Dashti, Masoumeh; Harris, Stephen J. et al. (2012) Besov priors for Bayesian inverse problems Inverse Problems and Imaging; Vol. 6; No. 2;
Schwab, C.; Stuart, A. M. (2012) Sparse determinisitc approximation of Bayesian inverse problems Inverse Problems; Vol. 28; No. 4;
Pinski, F. J.; Stuart, A. M. et al. (2012) Γ-Limit for Transition Paths of Maximal Probability Journal of Statistical Physics; Vol. 146; No. 5;
Cotter, S. L.; Dashti, M. et al. (2012) Variational data assimilation using targetted random walks International Journal for Numerical Methods in Fluids; Vol. 68; No. 4;
Pavliotis, Grigorios A.; Pokern, Yvo et al. (2012) Parameter estimation for multiscale diffusions: an overview Statistical Methods for Stochastic Differential Equations; Séminaire Européen de Statistique on “Statistics for Stochastic Differential Equations Models”, May 7-12, 2007 , Cartagena, Spain
Dashti, M.; Stuart, A. M. (2011) Uncertainty Quantification and Weak Approximation of an Elliptic Inverse Problem SIAM Journal on Numerical Analysis; Vol. 49; No. 6;
Brett, C. E. A.; Lam, K. F. et al. (2011) Stability of Filters for the Navier-Stokes Equation (Submitted)
Beskos, A.; Pinski, F. J. et al. (2011) Hybrid Monte Carlo on Hilbert spaces Stochastic Processes and their Applications; Vol. 121; No. 10;
Lee, Wonjung; McDougall, D. et al. (2011) Kalman filtering and smoothing for linear wave equations with model error Inverse Problems; Vol. 27; No. 9;
Melbourne, I.; Stuart, A. M. (2011) A note on diffusion limits of chaotic skew-product flows Nonlinearity; Vol. 24; No. 4;
Hairer, Martin; Stuart, Andrew M. et al. (2011) Sampling conditioned hypoelliptic diffusions Annals of Applied Probability; Vol. 21; No. 2;
Hairer, M.; Stuart, A. M. et al. (2011) Signal processing problems on function space: Bayesian formulation, stochastic PDEs and effective MCMC methods The Oxford Handbook of Nonlinear Filtering;
Nolen, James; Pavliotis, Grigorios A. et al. (2011) Multiscale modelling and inverse problems Numerical Analysis of Multiscale Problems; Series.Lecture Notes in Computational Science and Engineering; No. 83;
Fearnhead, Paul; Papaspiliopoulos, Omiros et al. (2010) Random-weight particle filtering of continuous time processes Journal of the Royal Statistical Society: Series B; Vol. 72; No. 4;
Fearnhead, Paul; Papaspiliopoulos, Omiros et al. (2010) Random-weight particle filtering of continuous time processes Statistical Methodology; Vol. 72; No. 4;
Pinski, F. J.; Stuart, A. M. (2010) Transition paths in molecules at finite temperature Journal of Chemical Physics; Vol. 132; No. 18;
Mattingly, J. C.; Stuart, A. M. et al. (2010) Convergence of numerical time-averaging and stationary measures via Poisson equations SIAM Journal of Numerical Analysis; Vol. 48; No. 2;
Stuart, A. M. (2010) Inverse problems: A Bayesian perspective Acta Numerica; Acta Numerica; Vol. 19;
Cotter, S. L.; Dashti, M. et al. (2010) Approximation of Bayesian Inverse Problems for PDEs SIAM Journal on Numerical Analysis; Vol. 48; No. 1;
Cotter, S. L.; Dashti, M. et al. (2009) Bayesian inverse problems for functions and applications to fluid mechanics Inverse Problems; Vol. 25; No. 11;
Pokern, Yvo; Stuart, Andrew M. et al. (2009) Remarks on Drift Estimation for Diffusion Processes Multiscale Modeling and Simulation; Vol. 8; No. 1;
Papavasiliou, A.; Pavliotis, G. A. et al. (2009) Maximum likelihood drift estimation for multiscale diffusions Stochastic Processes and their Applications; Vol. 119; No. 10;
Stuart, Andrew; Voss, Jochen (2009) Matrix Analysis and Algorithms
Beskos, Alexandros; Stuart, Andrew (2009) MCMC methods for sampling function space Sixth International Congress on Industrial and Applied Mathematics; Series.EMS Monographs in Mathematics; 6th International Congress on Industrial and Applied Mathematics, 16-20 July 2007 , Zürich, Switzerland
Beskos, Alexandros; Roberts, Gareth et al. (2009) Optimal scalings for local Metropolis–Hastings chains on nonproduct targets in high dimensions Annals of Applied Probability; Vol. 19; No. 3;
Hairer, Martin; Stuart, Andrew et al. (2009) Sampling conditioned diffusions Trends in Stochastic Analysis; Series.London Mathematical Society lecture note series; No. 353;
Pavliotis, G. A.; Stuart, A. M. et al. (2009) Calculating effective diffusivities in the limit of vanishing molecular diffusion Journal of Computational Physics; Vol. 288; No. 4;
Pokern, Yvo; Stuart, Andrew M. et al. (2009) Parameter estimation for partially observed hypo-elliptic diffusions Journal of the Royal Society: Series B (Statistical Methodology); Vol. 71; No. 1;
Pokern, Yvo; Stuart, Andrew M. et al. (2009) Parameter estimation for partially observed hypoelliptic diffusions Statistical Methodology; Vol. 71; Series.B; No. 1;
Beskos, Alexandros; Stuart, Andrew (2009) Computational Complexity of Metropolis-Hastings Methods in High Dimensions Monte Carlo and Quasi-Monte Carlo Methods 2008; Monte Carlo and Quasi-Monte Carlo Methods 2008, July 2008 , Montreal, Quebec
White, David; Stuart, Andrew (2009) Green’s Functions by Monte Carlo Monte Carlo and Quasi-Monte Carlo Methods 2008; Eighth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, July 6-11, 2008 , Montreal, Canada
Beskos, Alexandros; Roberts, Gareth et al. (2008) MCMC Methods for Diffusion Bridges Stochastics and Dynamics; Vol. 8; No. 3;
Apte, A.; Jones, C. K. R. T. et al. (2008) Data assimilation: Mathematical and statistical perspectives International Journal for Numerical Methods in Fluids; Vol. 56; No. 8;
Apte, A.; Jones, C. K. R. T. et al. (2008) A Bayesian approach to Lagrangian data assimilation Tellus A; Vol. 60; No. 2;
Gonzalez, Oscar; Stuart, Andrew M. (2008) A First Course in Continuum Mechanics Vol. 42; Series.Cambridge Texts in Applied Mathematics;
Pavliotis, Grigorios A.; Stuart, Andrew M. (2008) Multiscale Methods: Averaging and Homogenization Vol. 53; Series.Texts in Applied Mathematics;
Lamba, H.; Mattingly, J. C. et al. (2007) An adaptive Euler-Maruyama scheme for SDEs: convergence and stability IMA Journal of Numerical Analysis; Vol. 27; No. 3;
Apte, A.; Hairer, M. et al. (2007) Sampling the posterior: An approach to non-Gaussian data assimilation Physica D; Vol. 230; No. 1-2;
Pavliotis, G. A.; Stuart, A. M. (2007) Parameter Estimation for Multiscale Diffusions Journal of Statistical Physics; Vol. 127; No. 4;
Hairer, M.; Stuart, A. M. et al. (2007) Analysis of SPDEs arising in path sampling part II: The nonlinear case Annals of Applied Probability; Vol. 17; No. 5/6;
Pavliotis, G. A.; Stuart, A. M. et al. (2007) Homogenization for inertial particles in a random flow Communications in Mathematical Sciences; Vol. 5; No. 3;
Barkley, D.; Kevrekidis, I. G. et al. (2006) The Moment Map: Nonlinear Dynamics of Density Evolution via a Few Moments SIAM Journal on Applied Dynamical Systems; Vol. 5; No. 3;
Pavliotis, G. A.; Stuart, A. M. et al. (2006) Monte Carlo Studies of Effective Diffusivities for Inertial Particles Monte Carlo and Quasi-Monte Carlo Methods 2004; Sixth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, 7–10 June 2004 , Juan-les-Pins, France
Pavliotis, G. A.; Stuart, A. M. (2005) Analysis of White Noise Limits for Stochastic Systems with Two Fast Relaxation Times Multiscale Modeling and Simulation; Vol. 4; No. 1;
Pavliotis, G. A.; Stuart, A. M. (2005) Periodic homogenization for inertial particles Physica D; Vol. 204; No. 3-4;
Hairer, M.; Stuart, A. M. et al. (2005) Analysis of SPDEs arising in path sampling. Part I: The Gaussian case Communications in Mathematical Sciences; Vol. 3; No. 4;
Kupferman, R.; Stuart, A. M. (2004) Fitting SDE models to nonlinear Kac–Zwanzig heat bath models Physica D; Vol. 199; No. 3-4;
Stuart, Andrew M.; Voss, Jochen et al. (2004) Conditional Path Sampling of SDEs and the Langevin MCMC Method Communications in Mathematical Sciences; Vol. 2; No. 4;
Givon, Dror; Kupferman, Raz et al. (2004) Extracting macroscopic dynamics: model problems and algorithms Nonlinearity; Vol. 17; No. 6; 2002 Ron Diperna Memorial Lecture, 7 February 2002 , Berkeley, CA
Kupferman, R.; Pavliotis, G. A. et al. (2004) Itô versus Stratonovich white-noise limits for systems with inertia and colored multiplicative noise Physical Review E; Vol. 70; No. 3;
Pavliotis, G. A.; Stuart, A. M. (2003) White Noise Limits for Inertial Particles in a Random Field Multiscale Modeling and Simulation; Vol. 1; No. 4;
Huisinga, Wilhelm; Schütte, Christof et al. (2003) Extracting macroscopic stochastic dynamics: Model problems Communications on Pure and Applied Mathematics; Vol. 56; No. 2;
Higham, Desmond J.; Mao, Xuerong et al. (2003) Exponential Mean-Square Stability of Numerical Solutions to Stochastic Differential Equations LMS Journal of Computation and Mathematics; Vol. 6;
Kupferman, R.; Stuart, A. M. et al. (2002) Long-Term Behavior of Large Mechanical Systems with Random Initial Data Stochastics and Dynamics; Vol. 02; No. 04;
Sigurgeirsson, H.; Stuart, A. M. (2002) A model for preferential concentration Physics of Fluids; Vol. 14; No. 12;
Mattingly, J. C.; Stuart, A. M. et al. (2002) Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise Stochastic Processes and their Applications; Vol. 101; No. 2;
Higham, Desmond J.; Mao, Xuerong et al. (2002) Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations SIAM Journal on Numerical Analysis; Vol. 40; No. 3;
Estep, Donald J.; Stuart, Andrew M. (2002) The dynamical behavior of the discontinuous Galerkin method and related difference schemes Mathematics of Computation; Vol. 71; No. 239;
Sigurgeirsson, H.; Stuart, A. M. (2002) Inertial Particles in a Random Field Stochastics and Dynamics; Vol. 02; No. 02;
Humphries, A. R.; Stuart, A. M. (2002) Deterministic and random dynamical systems: theory and numerics Modern Methods in Scientific Computing and Applications; Series.NATO Science Series; No. 75;
Mattingly, J. C.; Stuart, A. M. (2002) Geometric Ergodicity of Some Hypo-Elliptic Diffusions for Particle Motions Markov Processes And Related Fields; Vol. 8; No. 2;
Sigurgeirsson, Hersir; Stuart, Andrew et al. (2001) Algorithms for Particle-Field Simulations with Collisions Journal of Computational Physics; Vol. 172; No. 2;
Cano, B.; Stuart, A. M. (2001) Underresolved Simulations of Heat Baths Journal of Computational Physics; Vol. 169; No. 1;
Cano, B.; Stuart, A. M. et al. (2001) Stiff Oscillatory Systems, Delta Jumps and White Noise Foundations of Computational Mathematics; Vol. 1; No. 1;
Sigurgeirsson, Hersir; Stuart, A. M. (2001) Statistics From Computations Foundations of Computational Mathematics; Series.London Mathematical Society lecture note series; No. 284;
Shardlow, T.; Stuart, A. M. (2000) A Perturbation Theory for Ergodic Markov Chains and Application to Numerical Approximations SIAM Journal on Numerical Analysis; Vol. 37; No. 4;
Lamba, Harbir; Stuart, Andrew (2000) Convergence Proofs for Numerical IVP Software Dynamics of Algorithms; Series.IMA Volumes in Mathematics and its Applications; No. 118;
Stuart, A. M.; Warren, J. O. (1999) Analysis and Experiments for a Computational Model of a Heat Bath Journal of Statistical Physics; Vol. 97; No. 3/4;
Sanz-Serna, J. M.; Stuart, A. M. (1999) Ergodicity of Dissipative Differential Equations Subject to Random Impulses Journal of Differential Equations; Vol. 155; No. 2;
Gonzalez, O.; Higham, D. J. et al. (1999) Qualitative properties of modified equations IMA Journal of Numerical Analysis; Vol. 19; No. 2;
Lamba, H.; Stuart, A. M. (1998) Convergence results for the MATLAB ODE23 routine BIT Numerical Mathematics; Vol. 38; No. 4;
Gander, Martin J.; Stuart, Andrew M. (1998) Space-Time Continuous Analysis of Waveform Relaxation for the Heat Equation SIAM Journal on Scientific Computing; Vol. 19; No. 6;
Budd, C. J.; Koomullil, G. P. et al. (1998) On the Solution of Convection-Diffusion Boundary Value Problems Using Equidistributed Grids SIAM Journal on Scientific Computing; Vol. 20; No. 2;
Jones, Don A.; Stuart, Andrew M. et al. (1998) Persistence of Invariant Sets for Dissipative Evolution Equations Journal of Mathematical Analysis and Applictions; Vol. 219; No. 2;
Higham, D. J.; Stuart, A. M. (1998) Analysis of the dynamics of local error control via a piecewise continuous residual BIT Numerical Mathematics; Vol. 38; No. 1;
Bjørhus, Morten; Stuart, Andrew M. (1997) Waveform relaxation as a dynamical system Mathematics of Computation; Vol. 66; No. 219;
Stuart, A. M. (1997) Probabilistic and deterministic convergence proofs for software for initial value problems Numerical Algorithms; Vol. 14; No. 1/3;
Stuart, Andrew (1997) Convergence and stability in the numerical approximation of dynamical systems The State of the Art in Numerical Analysis; Conference on the State of the Art in Numerical Analysis, April 1996 , University of York, England
Elliott, C. M.; Stuart, A. M. (1996) Viscous Cahn–Hilliard Equation II. Analysis Journal of Differential Equations; Vol. 128; No. 2;
Stuart, A. M.; Humphries, A. R. (1996) Dynamical Systems and Numerical Analysis Series.Cambridge Monographs on Applied and Computational Mathematics;
Jones, D. A.; Stuart, A. M. (1995) Attractive Invariant Manifolds under Approximation. Inertial Manifolds Journal of Differential Equations; Vol. 123; No. 2;
Stuart, A. M.; Humphries, A. R. (1995) The Essential Stability of Local Error Control for Dynamical Systems SIAM Journal on Numerical Analysis; Vol. 32; No. 6;
Estep, Donald J.; Stuart, Andrew M. (1995) The rate of error growth in Hamiltonian-conserving integrators Zeitschrift für Angewandte Mathematik und Physik; Vol. 46; No. 3;
Lord, Gabriel J.; Stuart, Andrew M. (1995) Discrete Gevrey regularity attractors and uppers–semicontinuity for a finite difference approximation to the Ginzburg–Landau equation Numerical Functional Analysis and Optimization; Vol. 16; No. 7-8;
Bai, F.; Elliott, C. M. et al. (1995) The viscous Cahn-Hilliard equation. I. Computations Nonlinearity; Vol. 8; No. 2;
Stuart, Andrew (1995) Perturbation Theory for Infinite Dimensional Dynamical Systems Theory and Numerics of Ordinary and Partial Differential Equations; Series.Advances in Numerical Analysis; No. 4;
Bai, Fengshan; Spence, Alastair et al. (1994) Numerical computations of coarsening in the one-dimensional Cahn-Hilliard model of phase separation Physica D; Vol. 78; No. 3-4;
Humphries, A. R.; Stuart, A. M. (1994) Runge–Kutta Methods for Dissipative and Gradient Dynamical Systems SIAM Journal on Numerical Analysis; Vol. 31; No. 5;
Budd, C. J.; Dold, J. W. et al. (1994) Blow-up in a System of Partial Differential Equations with Conserved First Integral. Part II: Problems with Convection SIAM Journal on Applied Mathematics; Vol. 54; No. 3;
Stuart, A. M.; Humphries, A. R. (1994) Model Problems in Numerical Stability Theory for Initial Value Problems SIAM Review; Vol. 36; No. 2;
Humphries, A. R.; Jones, D. A. et al. (1994) Approximation of dissipative partial differential equations over long time intervals Numerical Analysis 1993; Series.Pitman Research Notes in Mathematics Series ; No. 303; 15th Dundee Conference on Numerical Analysis, June-July, 1993 , Dundee, Scotalnd
Stuart, Andrew M. (1994) Numerical analysis of dynamical systems Acta Numerica; Vol. 3;
Elliott, C. M.; Stuart, A. M. (1993) The Global Dynamics of Discrete Semilinear Parabolic Equations SIAM Journal on Numerical Analysis; Vol. 30; No. 6; Dynamics of Numerics and Numerics of Dynamics, July 1990 , Bristol, UK
Chaplain, M. A. J.; Stuart, A. M. (1993) A model mechanism for the chemotactic response of endothelial cells to tumour angiogenesis factor Mathematical Medicine and Biology; Vol. 10; No. 3; Sixth IMA Conference on the Mathematical Theory of the Dynamics of Biological Systems, 1-3 July 1992 , Oxford, UK
Budd, Chris; Dold, Bill et al. (1993) Blowup in a Partial Differential Equation with Conserved First Integral SIAM Journal on Applied Mathematics; Vol. 53; No. 3;
Bai, Fengshan; Spence, Alastair et al. (1993) The Numerical Computation of Heteroclinic Connections in Systems of Gradient Partial Differential Equations SIAM Journal on Applied Mathematics; Vol. 53; No. 3;
Iserles, A.; Stuart, A. M. (1992) Unified approach to spurious solutions introduced by time discretization Part II: BDF-like methods IMA Journal of Numerical Analysis; Vol. 12; No. 4;
Griffiths, D. F.; Stuart, A. M. et al. (1992) Numerical Wave Propagation in an Advection Equation with a Nonlinear Source Term SIAM Journal on Numerical Analysis; Vol. 29; No. 5;
Sanz-Serna, J. M.; Stuart, A. M. (1992) A note on uniform in time error estimates for approximations to reaction-diffusion equations IMA Journal of Numerical Analysis; Vol. 12; No. 3;
Iserles, A.; Peplow, A. T. et al. (1991) A Unified Approach to Spurious Solutions Introduced by Time Discretisation. Part I: Basic Theory SIAM Journal on Numerical Analysis; Vol. 28; No. 6;
Stuart, A. M.; Peplow, A. T. (1991) The Dynamics of the Theta Method SIAM Journal on Scientific and Statistical Computing; Vol. 12; No. 6;
Chaplain, M. A. J.; Stuart, A. M. (1991) A Mathematical Model for the Diffusion of Tumour Angiogenesis Factor into the Surrounding Host Tissue Mathematical Medicine and Biology; Vol. 8; No. 3;
Stuart, Andrew M. (1991) Singular Limits in Free Boundary Problems Rocky Mountain Journal of Mathematics; Vol. 21; No. 2;
Stuart, A. M.; Floater, M. S. (1990) On the computation of blow-up European Journal of Applied Mathematics; Vol. 1; No. 01;
Stuart, Andrew (1990) The Global Attractor Under Discretisation Continuation and Bifurcations: Numerical Techniques and Applications; Series.NATO ASI Series; No. 313;
Stuart, Andrew (1989) Linear Instability Implies Spurious Periodic Solutions IMA Journal of Numerical Analysis; Vol. 9; No. 4;
Stuart, Andrew (1989) Nonlinear Instability in Dissipative Finite Difference Schemes SIAM Review; Vol. 31; No. 2;
Norbury, J.; Stuart, A. M. (1989) A Model for Porous-Medium Combustion Quarterly Journal of Mechanics and Applied Mathematics; Vol. 42; No. 1;
Stuart, A. M. (1989) Singular Free Boundary Problems and Local Bifurcation Theory SIAM Journal on Applied Mathematics; Vol. 49; No. 1;
Stuart, Andrew (1989) A Note on High/Low-Wave-Number Interactions in Spatially Discrete Parabolic Equations IMA Journal of Applied Mathematics; Vol. 42; No. 1;
Stuart, Andrew (1988) Similarity Solutions of a Heat Equation with Nonlinearly Varying Heat Capacity IMA Journal of Applied Mathematics; Vol. 40; No. 3;
Norbury, J.; Stuart, A. M. (1988) Travelling Combustion Waves in a Porous Medium. Part II—Stability SIAM Journal on Applied Mathematics; Vol. 48; No. 2;
Norbury, J.; Stuart, A. M. (1988) Travelling Combustion Waves in a Porous Medium. Part I—Existence SIAM Journal on Applied Mathematics; Vol. 48; No. 1;
Stuart, A. M. (1988) The Mathematics of Porous Medium Combustion Nonlinear Diffusion Equations and Their Equilibrium States II; Series.Mathematical Sciences Research Institute publications ; No. 13; Nonlinear Diffusion Equations and Their Equilibrium States II, August 25-September 12, 1986 , Berkeley, CA
Norbury, J.; Stuart, A. M. (1987) Parabolic Free Boundary Problems Arising in Porous Medium Combustion IMA Journal of Applied Mathematics; Vol. 39; No. 3;
Stuart, A. M. (1987) Existence of Solutions of a Two-Point Free-Boundary Problem Arising in the Theory of Porous Medium Combustion IMA Journal of Applied Mathematics; Vol. 38; No. 1;
Norbury, J.; Stuart, A. M. (1987) Volterra integral equations and a new Gronwall inequality (Part I: The linear case) Proceedings of the Royal Society of Edinburgh: Section A Mathematics; Vol. 106; No. 3-4;
Norbury, J.; Stuart, A. M. (1987) Volterra integral equations and a new Gronwall inequality (Part II: The nonlinear case) Proceedings of the Royal Society of Edinburgh: Section A Mathematics; Vol. 106; No. 3-4;