Andrew M. Stuart
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(Suggest an Edit or Addition)Andrew M. Stuart's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Inverse problems: A Bayesian perspective (2010) (1410)
- Multiscale Methods: Averaging and Homogenization (2008) (885)
- Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations (2002) (593)
- Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise (2002) (578)
- MCMC Methods for Functions: ModifyingOld Algorithms to Make Them Faster (2012) (526)
- The Bayesian Approach to Inverse Problems (2013) (498)
- Dynamical Systems And Numerical Analysis (1996) (484)
- A First Course in Continuum Mechanics (2008) (413)
- Extracting macroscopic dynamics: model problems and algorithms (2004) (388)
- Optimal tuning of the hybrid Monte Carlo algorithm (2010) (288)
- Ensemble Kalman methods for inverse problems (2012) (254)
- The global dynamics of discrete semilinear parabolic equations (1993) (245)
- Data Assimilation: A Mathematical Introduction (2015) (236)
- Space-Time Continuous Analysis of Waveform Relaxation for the Heat Equation (1998) (190)
- MCMC methods for diffusion bridges (2008) (184)
- Model Reduction and Neural Networks for Parametric PDEs (2020) (171)
- Analysis of the Ensemble Kalman Filter for Inverse Problems (2016) (164)
- Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions (2011) (163)
- Bayesian inverse problems for functions and applications to fluid mechanics (2009) (163)
- Convergence of Numerical Time-Averaging and Stationary Measures via Poisson Equations (2009) (158)
- Exponential mean square stability of numerical solutions to stochastic differential equations (2003) (152)
- MAP estimators and their consistency in Bayesian nonparametric inverse problems (2013) (146)
- Sampling the posterior: An approach to non-Gaussian data assimilation (2007) (135)
- Hybrid Monte Carlo on Hilbert spaces (2011) (130)
- ANALYSIS OF SPDES ARISING IN PATH SAMPLING PART II: THE NONLINEAR CASE (2006) (129)
- Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler (2019) (119)
- Runge-Kutta methods for dissipative and gradient dynamical systems (1994) (117)
- Parameter Estimation for Multiscale Diffusions (2006) (115)
- Approximation of Bayesian Inverse Problems for PDEs (2009) (114)
- Sparse deterministic approximation of Bayesian inverse problems (2011) (112)
- Well-posedness and accuracy of the ensemble Kalman filter in discrete and continuous time (2013) (112)
- Importance Sampling: Intrinsic Dimension and Computational Cost (2015) (111)
- Viscous Cahn–Hilliard Equation II. Analysis (1996) (109)
- Optimal scalings for local Metropolis--Hastings chains on nonproduct targets in high dimensions (2009) (108)
- Evaluating Data Assimilation Algorithms (2011) (107)
- Geometric MCMC for infinite-dimensional inverse problems (2016) (106)
- Diffusion limits of the random walk metropolis algorithm in high dimensions (2010) (103)
- Conditional Path Sampling of SDEs and the Langevin MCMC Method (2004) (101)
- Optimal Scaling and Diffusion Limits for the Langevin Algorithm in High Dimensions (2011) (100)
- How Deep Are Deep Gaussian Processes? (2017) (99)
- Itô versus Stratonovich white-noise limits for systems with inertia and colored multiplicative noise. (2004) (99)
- Complexity analysis of accelerated MCMC methods for Bayesian inversion (2012) (98)
- Besov priors for Bayesian inverse problems (2011) (97)
- Posterior consistency for Gaussian process approximations of Bayesian posterior distributions (2016) (96)
- Analysis of SPDEs arising in path sampling. Part I: The Gaussian case (2005) (93)
- Uncertainty Quantification and Weak Approximation of an Elliptic Inverse Problem (2011) (91)
- Model Problems in Numerical Stability Theory for Initial Value Problems (1994) (89)
- The Random Feature Model for Input-Output Maps between Banach Spaces (2020) (86)
- Ensemble Kalman inversion: a derivative-free technique for machine learning tasks (2018) (86)
- Hierarchical Bayesian level set inversion (2016) (84)
- Algorithms for particle-field simulations with collisions (2001) (82)
- A note on diffusion limits of chaotic skew-product flows (2011) (81)
- Data assimilation: Mathematical and statistical perspectives (2008) (81)
- Posterior Contraction Rates for the Bayesian Approach to Linear Ill-Posed Inverse Problems (2012) (80)
- The viscous Cahn-Hilliard equation. I. Computations (1995) (79)
- Statistical analysis of differential equations: introducing probability measures on numerical solutions (2016) (78)
- An adaptive Euler-Maruyama scheme for SDEs: convergence and stability (2006) (76)
- Nonparametric estimation of diffusions: a differential equations approach (2012) (74)
- Blowup in a Partial Differential Equation with Conserved First Integral (1993) (72)
- Well-posed Bayesian geometric inverse problems arising in subsurface flow (2014) (71)
- Numerical wave propagation in an advection equation with a nonlinear source term (1992) (70)
- Geometric Ergodicity of Some Hypo-Elliptic Diffusions for Particle Motions (2002) (69)
- Sequential Monte Carlo methods for Bayesian elliptic inverse problems (2014) (69)
- Accuracy and stability of the continuous-time 3DVAR filter for the Navier–Stokes equation (2012) (67)
- Evaluation of Gaussian approximations for data assimilation in reservoir models (2012) (67)
- Convergence analysis of ensemble Kalman inversion: the linear, noisy case (2017) (66)
- A Bayesian Level Set Method for Geometric Inverse Problems (2015) (66)
- On the computation of blow-up (1990) (63)
- Parameter estimation for partially observed hypoelliptic diffusions (2007) (62)
- Maximum likelihood drift estimation for multiscale diffusions (2008) (61)
- A model for preferential concentration (2002) (60)
- A Function Space HMC Algorithm With Second Order Langevin Diffusion Limit (2013) (60)
- Random‐weight particle filtering of continuous time processes (2010) (60)
- Parameterizations for ensemble Kalman inversion (2017) (57)
- A unified approach to spurious solutions introduced by time discretization. Part I: basic theory (1991) (56)
- A Perturbation Theory for Ergodic Markov Chains and Application to Numerical Approximations (2000) (56)
- Calibrate, emulate, sample (2020) (55)
- Kullback-Leibler Approximation for Probability Measures on Infinite Dimensional Spaces (2013) (55)
- Tikhonov Regularization within Ensemble Kalman Inversion (2019) (54)
- Posterior consistency via precision operators for Bayesian nonparametric drift estimation in SDEs (2012) (54)
- The Bayesian Formulation of EIT: Analysis and Algorithms (2015) (53)
- Analysis of the Gibbs Sampler for Hierarchical Inverse Problems (2013) (53)
- Quasi-Monte Carlo and Multilevel Monte Carlo Methods for Computing Posterior Expectations in Elliptic Inverse Problems (2016) (53)
- Periodic homogenization for inertial particles (2005) (53)
- Analysis of the 3DVAR filter for the partially observed Lorenz'63 model (2012) (52)
- Solving and Learning Nonlinear PDEs with Gaussian Processes (2021) (52)
- A Bayesian approach to Lagrangian data assimilation (2008) (52)
- MCMC methods for sampling function space (2009) (51)
- Algorithms for Kullback-Leibler Approximation of Probability Measures in Infinite Dimensions (2014) (50)
- Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms (2018) (49)
- Uncertainty Quantification in Graph-Based Classification of High Dimensional Data (2017) (47)
- Iterative updating of model error for Bayesian inversion (2017) (45)
- LONG-TERM BEHAVIOUR OF LARGE MECHANICAL SYSTEMS WITH RANDOM INITIAL DATA (2002) (44)
- Ergodicity of Dissipative Differential Equations Subject to Random Impulses (1999) (42)
- The Numerical Computation of Heteroclinic Connections in Systems of Gradient Partial Differential Equations (1993) (40)
- Ensemble Kalman methods with constraints (2019) (39)
- Nonlinear Instability in Dissipative Finite Difference Schemes (1989) (39)
- A model for porous-medium combustion (1989) (39)
- Signal processing problems on function space: Bayesian formulation, stochastic PDEs and effective MCMC methods (2011) (39)
- Numerical analysis of dynamical systems (1994) (38)
- Accuracy and stability of filters for dissipative PDEs (2012) (37)
- White Noise Limits for Inertial Particles in a Random Field (2003) (37)
- Extracting macroscopic stochastic dynamics: Model problems (2003) (37)
- SPDE limits of the random walk Metropolis algorithm in high dimensions (2009) (35)
- Analysis and Experiments for a Computational Model of a Heat Bath (1999) (35)
- Bayesian posterior contraction rates for linear severely ill-posed inverse problems (2012) (35)
- Transition paths in molecules at finite temperature (2010) (32)
- The Dynamics of the Theta Method (1991) (32)
- Analysis of White Noise Limits for Stochastic Systems with Two Fast Relaxation Times (2005) (31)
- Importance Sampling: Computational Complexity and Intrinsic Dimension (2015) (31)
- Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems (2014) (30)
- Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype (2018) (30)
- Calculating effective diffusivities in the limit of vanishing molecular diffusion (2009) (29)
- Volterra integral equations and a new Gronwall inequality (Part II: The nonlinear case) (1987) (29)
- Parameter Estimation for Macroscopic Pedestrian Dynamics Models from Microscopic Data (2018) (28)
- Calibration and Uncertainty Quantification of Convective Parameters in an Idealized GCM (2020) (28)
- Attractive Invariant Manifolds under Approximation. Inertial Manifolds (1995) (28)
- Variational data assimilation using targetted random walks (2012) (28)
- Blow-up in a System of Partial Differential Equations with Conserved First Integral. Part II: Problems with Convection (1994) (28)
- The rate of error growth in Hamiltonian-conserving integrators (1995) (28)
- Perturbation Theory for Infinite Dimensional Dynamical Systems (1995) (27)
- The Moment Map: Nonlinear Dynamics of Density Evolution via a Few Moments (2005) (27)
- Sampling conditioned diffusions (2009) (26)
- Strong convergence rates of probabilistic integrators for ordinary differential equations (2017) (26)
- Travelling combustion waves in a porous medium. Part 1—existence (1988) (26)
- Probability Theory and Stochastic Processes (2008) (25)
- A note on uniform in time error estimates for approximations to reaction-diffusion equations (1992) (25)
- An MCMC method for diffusion bridges (2008) (24)
- The essential stability of local error control for dynamical systems (1995) (24)
- Analysis of the dynamics of local error control via a piecewise continuous residual (1998) (23)
- Computational Complexity of Metropolis-Hastings Methods in High Dimensions (2009) (22)
- The dynamical behavior of the discontinuous Galerkin method and related difference schemes (2001) (22)
- Homogenization for inertial particles in a random flow (2007) (22)
- A Framework for Machine Learning of Model Error in Dynamical Systems (2021) (22)
- Inverse Problems and Data Assimilation. (2018) (22)
- Gaussian Approximations for Probability Measures on Rd (2017) (21)
- Filter accuracy for the Lorenz 96 model: Fixed versus adaptive observation operators (2016) (20)
- Consensus‐based sampling (2021) (20)
- Iterated Kalman methodology for inverse problems (2021) (20)
- Sampling conditioned hypoelliptic diffusions (2009) (20)
- Linear Instability Implies Spurious Periodic Solutions (1989) (20)
- Probability Measures for Numerical Solutions of Differential Equations (2015) (20)
- Remarks on Drift Estimation for Diffusion Processes (2009) (20)
- Numerical computations of coarsening in the one-dimensional Cahn-Hilliard model of phase separation (1994) (19)
- Convergence Rates for Learning Linear Operators from Noisy Data (2021) (19)
- Persistence of Invariant Sets for Dissipative Evolution Equations (1998) (19)
- Multiscale modelling and inverse problems (2010) (19)
- POSTERIOR CONSISTENCY OF THE BAYESIAN APPROACH TO LINEAR ILL-POSED INVERSE PROBLEMS (2012) (19)
- Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation (2020) (18)
- Stiff Oscillatory Systems, Delta Jumps and White Noise (2001) (18)
- Noisy gradient flow from a random walk in Hilbert space (2011) (18)
- Learning stochastic closures using ensemble Kalman inversion (2020) (18)
- Consistency of semi-supervised learning algorithms on graphs: Probit and one-hot methods (2019) (18)
- Uncertainty Quantification in the Classification of High Dimensional Data (2017) (18)
- The Cost-Accuracy Trade-Off In Operator Learning With Neural Networks (2022) (18)
- Dimension-Robust MCMC in Bayesian Inverse Problems (2018) (18)
- INERTIAL PARTICLES IN A RANDOM FIELD (2002) (17)
- Gaussian Approximations for Transition Paths in Brownian Dynamics (2016) (17)
- Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods (2021) (17)
- MAP estimators for piecewise continuous inversion (2015) (17)
- Continuous Time Analysis of Momentum Methods (2019) (17)
- Unified approach to spurious solutions introduced by time discretization Part II: BDF-like methods (1992) (16)
- Fitting SDE models to nonlinear Kac–Zwanzig heat bath models (2004) (16)
- Ensemble Kalman inversion for sparse learning of dynamical systems from time-averaged data (2020) (15)
- Discrete Gevrey regularity attractors and uppers–semicontinuity for a finite difference approximation to the Ginzburg–Landau equation (1995) (15)
- Convergence results for the MATLAB ode23 routine (1998) (15)
- Inverse Problems and Uncertainty Quantification (2014) (15)
- Sparse MCMC gpc finite element methods for Bayesian inverse problems (2012) (15)
- Travelling combustion waves in a porous medium. Part II—Stability (1988) (14)
- A Bayesian Approach to Data Assimilation (2005) (14)
- Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency (2019) (14)
- On the Solution of Convection-Diffusion Boundary Value Problems Using Equidistributed Grids (1998) (14)
- Γ-Limit for Transition Paths of Maximal Probability (2011) (13)
- GAUSSIAN APPROXIMATIONS FOR PROBABILITY MEASURES ON R (2016) (13)
- Weak Error Estimates for Trajectories of SPDEs Under Spectral Galerkin Discretization (2016) (13)
- Parabolic Free Boundary Problems Arising in Porous Medium Combustion (1987) (13)
- Parameter estimation for multiscale diffusions : an overview (2012) (13)
- Waveform relaxation as a dynamical system (1997) (13)
- Efficient derivative-free Bayesian inference for large-scale inverse problems (2022) (13)
- Spectral analysis of weighted Laplacians arising in data clustering (2019) (13)
- Robust MCMC Sampling with Non-Gaussian and Hierarchical Priors in High Dimensions (2018) (13)
- Determining white noise forcing from Eulerian observations in the Navier-Stokes equation (2013) (13)
- Deterministic and random dynamical systems: theory and numerics (2002) (12)
- Diffusion limit for the random walk Metropolis algorithm out of stationarity (2014) (12)
- Inverse Optimal Transport (2019) (12)
- Statistics From Computations (2001) (12)
- Probabilistic and deterministic convergence proofs for software for initial value problems (1997) (12)
- Gaussian Approximations of Small Noise Diffusions in Kullback-Leibler Divergence (2016) (11)
- Controlling Unpredictability with Observations in the Partially Observed Lorenz '96 Model (2014) (11)
- Filter Based Methods For Statistical Linear Inverse Problems (2015) (10)
- Non-stationary phase of the MALA algorithm (2016) (10)
- Diffusive Optical Tomography in the Bayesian Framework (2019) (10)
- Analysis Of Momentum Methods (2019) (10)
- Monte Carlo Studies of Effective Diffusivities for Inertial Particles (2006) (10)
- Imposing Sparsity Within Ensemble Kalman Inversion (2020) (10)
- Ensemble Kalman Methods: A Mean Field Perspective (2022) (10)
- Uncertainty quantification for semi-supervised multi-class classification in image processing and ego-motion analysis of body-worn videos (2019) (9)
- On the qualitative properties of modified equations (1997) (9)
- Optimal Proposal Design for Random Walk Type Metropolis Algorithms with Gaussian Random Field Priors (2011) (9)
- Unscented Kalman Inversion (2021) (9)
- Approximation of dissipative partial differential equations over long time intervals (1994) (9)
- Kalman filtering and smoothing for linear wave equations with model error (2011) (9)
- Drift Estimation of Multiscale Diffusions Based on Filtered Data (2020) (9)
- Stability of Filters for the Navier-Stokes Equation (2011) (9)
- Gradient Structure Of The Ensemble Kalman Flow With Noise (2019) (9)
- Underresolved simulations of heat baths (2001) (8)
- Derivative-Free Bayesian Inversion Using Multiscale Dynamics (2021) (8)
- The Acceptance Probability of the Hybrid Monte Carlo Method in High‐Dimensional Problems (2010) (8)
- Optimal scalings of Metropolis-Hastings algorithms for non-product targets in high dimensions (2009) (8)
- A Simple Modeling Framework For Prediction In The Human Glucose-Insulin System (2019) (7)
- On the random walk metropolis algorithm for Gaussian random field priors and the gradient flow (2011) (7)
- Qualitative properties of modified equations (1999) (7)
- Gaussian Approximations for Probability Measures on $\mathbf{R}^d$ (2016) (6)
- Matrix analysis and algorithms (2009) (6)
- Convergence Proofs for Numerical IVP Software (2000) (6)
- Ergodicity and Accuracy of Optimal Particle Filters for Bayesian Data Assimilation (2016) (5)
- A Multiscale Analysis of Diffusions on Rapidly Varying Surfaces (2013) (5)
- Posterior consistency of semi-supervised regression on graphs (2020) (5)
- The Global Attractor Under Discretisation (1990) (5)
- A Note on High/Low-Wave-Number Interactions in Spatially Discrete Parabolic Equations (1989) (5)
- Derivation and analysis of simplified filters (2017) (5)
- Uncertainty Quantification in Bayesian Inversion (2014) (4)
- Mathematical and Algorithmic Aspects of Data Assimilation in the Geosciences (2017) (4)
- Offline and online data assimilation for real-time blood glucose forecasting in type 2 diabetes (2017) (4)
- A First Course in Continuum Mechanics: Preface (2008) (4)
- MCMC for the Evaluation of Gaussian Approximations to Bayesian Inverse Problems in Groundwater Flow (2012) (3)
- Extracting Macroscopic Stochastic Dynamics (2003) (3)
- The Mathematics of Porous Medium Combustion (1988) (3)
- Ensemble‐Based Experimental Design for Targeting Data Acquisition to Inform Climate Models (2022) (3)
- Reconciling Bayesian and Total Variation Methods for Binary Inversion (2017) (3)
- Differential Equations Subject to Random Impulses (1997) (3)
- A perturbation theory for ergodic properties of Markov chains (1998) (3)
- TIKHONOV REGULARIZATION WITHIN ENSEMBLE KALMAN INVERSION\ast (2020) (3)
- Approximation of inverse problems (2009) (3)
- Reconciling Bayesian and Perimeter Regularization for Binary Inversion (2017) (3)
- Existence of Solutions of a Two-Point Free-Boundary Problem Arising in the Theory of Porous Medium Combustion (1987) (3)
- Mathematical and Algorithmic Aspects of Atmosphere-Ocean Data Assimilation (2012) (3)
- An analysis of local error control for dissipative, contractive and gradient dynamical systems (1992) (3)
- Random-weight particle filtering of continuous time (2010) (3)
- FAST COMMUNICATION CONDITIONAL PATH SAMPLING OF SDES AND THE LANGEVIN (2004) (2)
- The moment map (2020) (2)
- Correction to: A note on diusion limits of chaotic skew-product ows (2015) (2)
- Filtering systems of coupled stochastic differential equations partially observed at high frequency (2007) (2)
- Learning macroscopic internal variables and history dependence from microscopic models (2022) (2)
- Numerical Analysis of Evolution Equations. (1997) (2)
- The Nonlocal Neural Operator: Universal Approximation (2023) (2)
- Continuous Time: Filtering Algorithms (2015) (2)
- Data Assimilation and Inverse Problems (2018) (2)
- Qualitative properties of modi"ed equations (1999) (2)
- Mathematics, Statistics and Data Science (2016) (2)
- ON THE SOLUTION OF CONVECTION-DIFFUSION BOUNDARY VALUE PROBLEMS BY GRID ADAPTATION (1995) (2)
- Extracting Macroscopic Dynamics : Model Problems & Algorithms (2003) (2)
- Bayesian Formulations of Multidimensional Barcode Inversion (2017) (1)
- On the Qualitative Properties of Modi (1)
- Attractive Invariant Manifolds under Approximation Part I: Inertial Manifolds (1995) (1)
- Second Order Ensemble Langevin Method for Sampling and Inverse Problems (2022) (1)
- A First Course in Continuum Mechanics: Continuum Mass and Force Concepts (2008) (1)
- Discrete Time: Formulation (2015) (1)
- Non parametric Bayesian drift estimation for one-dimensional diffusion processes (2009) (1)
- Kalman filtering for linear wave equations with model error (2011) (1)
- Mathematical foundations of data assimilation problems arising in fluid mechanics (2008) (1)
- Singular Limits in Free Boundary Problems (1991) (1)
- Homogenization for Elliptic PDEs (2008) (1)
- Derivation and Analysis of Simplified Filters for Complex Dynamical Systems (2015) (1)
- A free boundary problem arising in smoulder combustion (1992) (1)
- OPTIMAL PROPOSALS FOR MCMC METHODS (2010) (1)
- Convergence Analysis of the Ensemble Kalman Filter for Inverse Problems: the Noisy Case (2017) (1)
- Learning Chaotic Dynamics in Dissipative Systems (2022) (1)
- Singular free boundary problems and local bifurcation theory (1989) (1)
- Discrete Time: Filtering Algorithms (2015) (0)
- Homogenization for SDEs: The Convergence Theorem (2008) (0)
- Diffusive Optical Tomography in the Bayesian Framework | Multiscale Modeling & Simulation | Vol. 18, No. 2 | Society for Industrial and Applied Mathematics (2020) (0)
- Weak approximation of an elliptic inverse problem (2010) (0)
- Averaging for Linear Transport and Parabolic PDEs: The Convergence Theorem (2008) (0)
- Optimal scaling of MCMC for conditioned diffusions (2008) (0)
- Stochastic Differential Equations (2008) (0)
- Data assimilation for Navier-Stokes (2011) (0)
- Determining white noise forcing from Eulerian observations in the Navier-Stokes equation (2014) (0)
- Solution of discrete convection–diffusion problems (2014) (0)
- A First Course in Continuum Mechanics: Tensor Algebra (2008) (0)
- Similarity Solutions of a Heat Equation with Nonlinearly Varying Heat Capacity (1988) (0)
- Γ-Limit for Transition Paths of Maximal Probability (2012) (0)
- Hierarchical Bayesian level set inversion (2016) (0)
- Probing Probability Measures In High Dimensions (2012) (0)
- A First Course in Continuum Mechanics: Balance Laws (2008) (0)
- DIFFUSIVE OPTICAL TOMOGRAPHY IN THE BAYESIAN FRAMEWORK\ast (2020) (0)
- Optimal tuning of MCMC algorithms in infinite dimensions (2008) (0)
- A Multiscale Analysis of Diffusions on Rapidly Varying Surfaces (2015) (0)
- Discrete Time: MATLAB Programs (2015) (0)
- The convection–diffusion equation (2014) (0)
- MCMC methods in high dimension. (2009) (0)
- Accuracy and Stability of Filters for Data Assimilation (2018) (0)
- A ug 2 00 9 Sampling Conditioned Hypoelliptic Diffusions (2009) (0)
- Using mechanistic machine learning to forecast glucose and infer physiologic phenotypes in the ICU: what is possible and what are the challenges (2018) (0)
- Averaging for Markov Chains (2008) (0)
- A First Course in Continuum Mechanics: Bibliography (2008) (0)
- Corrigendum: Volterra integral equations and a new Gronwall inequality (Part 1: The linear case) (1989) (0)
- Complete Solutions Manual for A First Course in Continuum Mechanics (2017) (0)
- Continuous Time: Formulation (2015) (0)
- PR ] 2 3 Ju n 20 17 Gaussian Approximations for Probability Measures on R (2017) (0)
- Ja n 20 06 Analysis of SPDEs Arising in Path Sampling Part II : The Nonlinear Case February 27 , 2008 (0)
- Isothermal Solid Mechanics (2008) (0)
- Discrete Time: Smoothing Algorithms (2015) (0)
- The hybrid Monte Carlo algorithm on Hilbert space (2010) (0)
- A First Course in Continuum Mechanics: Thermal Solid Mechanics (2008) (0)
- The 3DVAR filter for the Navier-Stokes equation: Accuracy and stability in the limit of high-frequency observations (2012) (0)
- Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes (2016) (0)
- Thermal Fluid Mechanics (2008) (0)
- An elliptic inverse problem arising in groundater flow (2011) (0)
- ACCURATE DATA ASSIMILATION FOR CHAOTIC DYNAMICAL SYSTEMS (2013) (0)
- Convergence and stability in the numerical approximation ofdynamical systems (1997) (0)
- Homogenization for Parabolic PDEs (2008) (0)
- Estimating model error using sparsity-promoting ensemble Kalman inversion (2020) (0)
- Averaging of Stochastic Differential Equations: Kurtz's Theorem Revisited (2004) (0)
- INVERSE OPTIMAL TRANSPORT \ast (2020) (0)
- Green’s Functions by Monte Carlo (2009) (0)
- N A ] 11 S ep 2 00 9 Approximation of Bayesian Inverse Problems for PDEs September 11 (2009) (0)
- The Stokes equations (2014) (0)
- Invariant Manifolds for ODEs (2008) (0)
- Lessons learned from assimilating knowledge into machine learning to forecast and control glucose in a critical care setting (2020) (0)
- 1991 Leiden Conf on Nonlinear Diffusion (1991) (0)
- Bayesian inverse problems in PDEs (2009) (0)
- Data Assimilation: New Challenges in Random and Stochastic Dynamical Systems (2015) (0)
- Data assimilation : inverse problems in dynamical systems (2008) (0)
- Hybrid Monte Carlo : geometric integration and statistics (2010) (0)
- O C ] 1 M ar 2 01 3 Ensemble Kalman Methods for Inverse Problems (2013) (0)
- Derivative-Free Bayesian Inversion Using Multiscale Dynamics | SIAM Journal on Applied Dynamical Systems | Vol. 21, No. 1 | Society for Industrial and Applied Mathematics (2022) (0)
- The Ensemble Kalman Filter in the Near-Gaussian Setting (2022) (0)
- A First Course in Continuum Mechanics: Tensor Calculus (2008) (0)
- Solution of discrete Poisson problems (2014) (0)
- Sti Oscillatory Systems , Delta Jumps and WhiteNoiseB (2011) (0)
- Noisy gradient flow from a random walk in Hilbert space (2014) (0)
- Non-stationary phase of the MALA algorithm (2018) (0)
- Explorer Uncertainty quantification in graph-based classification of high dimensional data (2018) (0)
- Kalman filtering and smoothing for an advection equation with model error (2011) (0)
- Why predicting postprandial glucose using self-monitoring data is difficult (2017) (0)
- Continuous Time: Smoothing Algorithms (2015) (0)
- A P ] 8 F eb 2 01 2 Sparse Deterministic Approximation of Bayesian Inverse Problems (0)
- Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance (2023) (0)
- Infinite Dimensional Random Dynamical Systems and Their Applications (2008) (0)
- Averaging for Markov Chains: The Convergence Theorem (2008) (0)
- Averaging of Stochastic Differential Equations (2004) (0)
- Averaging for Linear Transport and Parabolic PDEs (2008) (0)
- Averaging for SDEs: The Convergence Theorem (2008) (0)
- VARIATIONAL DATA ASSIMILATION USINGTARGETTED RANDOMWALKS 1 Variational Data Assimilation Using Targetted Random Walks (2010) (0)
- Homogenization for Elliptic PDEs: The Convergence Theorem (2008) (0)
- A mathematical framework for data assimilation (2009) (0)
- A First Course in Continuum Mechanics: Isothermal Fluid Mechanics (2008) (0)
- Homogenization for ODEs and SDEs (2008) (0)
- A First Course in Continuum Mechanics: Kinematics (2008) (0)
- Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures (2023) (0)
- Continuous Time: MATLAB Programs (2015) (0)
- Sequential Monte Carlo methods for Bayesian elliptic inverse problems (2015) (0)
- Bayesian well-posedness for inverse problems (2010) (0)
- 28 M ar 2 00 6 PARAMETER ESTIMATION FOR MULTISCALE DIFFUSIONS (0)
- Filtering the Navier-Stokes equation (2011) (0)
- The Mean Field Ensemble Kalman Filter: Near-Gaussian Setting (2022) (0)
- Invariant Manifolds for ODEs: The Convergence Theorem (2008) (0)
- Partial Differential Equations (2008) (0)
- Homogenization of elasticity problems on periodic composite structures (2016) (0)
- Averaging for ODEs and SDEs (2008) (0)
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