Andrew M. Stuart

According to our database1, Andrew M. Stuart authored at least 65 papers between 1989 and 2021.

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PhD thesis 


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Calibrate, emulate, sample.
J. Comput. Phys., 2021

Reconciling Bayesian and Perimeter Regularization for Binary Inversion.
SIAM J. Sci. Comput., 2020

Tikhonov Regularization within Ensemble Kalman Inversion.
SIAM J. Numer. Anal., 2020

Inverse Optimal Transport.
SIAM J. Appl. Math., 2020

Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler.
SIAM J. Appl. Dyn. Syst., 2020

Consistency of Semi-Supervised Learning Algorithms on Graphs: Probit and One-Hot Methods.
J. Mach. Learn. Res., 2020

Fourier Neural Operator for Parametric Partial Differential Equations.
CoRR, 2020

Drift Estimation of Multiscale Diffusions Based on Filtered Data.
CoRR, 2020

Posterior Consistency of Semi-Supervised Regression on Graphs.
CoRR, 2020

Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation.
CoRR, 2020

The Random Feature Model for Input-Output Maps between Banach Spaces.
CoRR, 2020

Model Reduction and Neural Networks for Parametric PDEs.
CoRR, 2020

Neural Operator: Graph Kernel Network for Partial Differential Equations.
CoRR, 2020

Multipole Graph Neural Operator for Parametric Partial Differential Equations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Parameter Estimation for Macroscopic Pedestrian Dynamics Models from Microscopic Data.
SIAM J. Appl. Math., 2019

Strong convergence rates of probabilistic integrators for ordinary differential equations.
Stat. Comput., 2019

Analysis Of Momentum Methods.
CoRR, 2019

Uncertainty quantification for semi-supervised multi-class classification in image processing and ego-motion analysis of body-worn videos.
Proceedings of the Image Processing: Algorithms and Systems XVII, 2019

Posterior consistency for Gaussian process approximations of Bayesian posterior distributions.
Math. Comput., 2018

Uncertainty Quantification in Graph-Based Classification of High Dimensional Data.
SIAM/ASA J. Uncertain. Quantification, 2018

How Deep Are Deep Gaussian Processes?
J. Mach. Learn. Res., 2018

Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.
J. Am. Medical Informatics Assoc., 2018

Ensemble Kalman Inversion: A Derivative-Free Technique For Machine Learning Tasks.
CoRR, 2018

Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms.
CoRR, 2018

Using mechanistic machine learning to forecast glucose and infer physiologic phenotypes in the ICU: what is possible and what are the challenges.
Proceedings of the AMIA 2018, 2018

Analysis of the Ensemble Kalman Filter for Inverse Problems.
SIAM J. Numer. Anal., 2017

Gaussian Approximations for Transition Paths in Brownian Dynamics.
SIAM J. Math. Anal., 2017

Hierarchical Bayesian level set inversion.
Stat. Comput., 2017

Statistical analysis of differential equations: introducing probability measures on numerical solutions.
Stat. Comput., 2017

Quasi-Monte Carlo and Multilevel Monte Carlo Methods for Computing Posterior Expectations in Elliptic Inverse Problems.
SIAM/ASA J. Uncertain. Quantification, 2017

Gaussian Approximations for Probability Measures on R<sup>d</sup>.
SIAM/ASA J. Uncertain. Quantification, 2017

Geometric MCMC for infinite-dimensional inverse problems.
J. Comput. Phys., 2017

Uncertainty Quantification in the Classification of High Dimensional Data.
CoRR, 2017

Why predicting postprandial glucose using self-monitoring data is difficult.
Proceedings of the AMIA 2017, 2017

Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes.
Proceedings of the AMIA 2016, 2016

Algorithms for Kullback-Leibler Approximation of Probability Measures in Infinite Dimensions.
SIAM J. Sci. Comput., 2015

Kullback-Leibler Approximation for Probability Measures on Infinite Dimensional Spaces.
SIAM J. Math. Anal., 2015

Sequential Monte Carlo methods for Bayesian elliptic inverse problems.
Stat. Comput., 2015

Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems.
SIAM/ASA J. Uncertain. Quantification, 2015

A Multiscale Analysis of Diffusions on Rapidly Varying Surfaces.
J. Nonlinear Sci., 2015

Analysis of the Gibbs Sampler for Hierarchical Inverse Problems.
SIAM/ASA J. Uncertain. Quantification, 2014

Uncertainty Quantification and Weak Approximation of an Elliptic Inverse Problem.
SIAM J. Numer. Anal., 2011

Evaluating Data Assimilation Algorithms
CoRR, 2011

Convergence of Numerical Time-Averaging and Stationary Measures via Poisson Equations.
SIAM J. Numer. Anal., 2010

Approximation of Bayesian Inverse Problems for PDEs.
SIAM J. Numer. Anal., 2010

Inverse problems: A Bayesian perspective.
Acta Numer., 2010

Remarks on Drift Estimation for Diffusion Processes.
Multiscale Model. Simul., 2009

Calculating effective diffusivities in the limit of vanishing molecular diffusion.
J. Comput. Phys., 2009

The Moment Map: Nonlinear Dynamics of Density Evolution via a Few Moments.
SIAM J. Appl. Dyn. Syst., 2006

Analysis of White Noise Limits for Stochastic Systems with Two Fast Relaxation Times.
Multiscale Model. Simul., 2005

White Noise Limits for Inertial Particles in a Random Field.
Multiscale Model. Simul., 2003

Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations.
SIAM J. Numer. Anal., 2002

The dynamical behavior of the discontinuous Galerkin method and related difference schemes.
Math. Comput., 2002

Stiff Oscillatory Systems, Delta Jumps and White Noise.
Found. Comput. Math., 2001

A Perturbation Theory for Ergodic Markov Chains and Application to Numerical Approximations.
SIAM J. Numer. Anal., 2000

Space-Time Continuous Analysis of Waveform Relaxation for the Heat Equation.
SIAM J. Sci. Comput., 1998

On the Solution of Convection-Diffusion Boundary Value Problems Using Equidistributed Grids.
SIAM J. Sci. Comput., 1998

Probabilistic and deterministic convergence proofs for software for initial value problems.
Numer. Algorithms, 1997

Waveform relaxation as a dynamical system.
Math. Comput., 1997

Model Problems in Numerical Stability Theory for Initial Value Problems.
SIAM Rev., 1994

Blow-up in a System of Partial Differential Equations with Conserved First Integral. Part II: Problems with Convection.
SIAM J. Appl. Math., 1994

Blowup in a Partial Differential Equation with Conserved First Integral.
SIAM J. Appl. Math., 1993

The Numerical Computation of Heteroclinic Connections in Systems of Gradient Partial Differential Equations.
SIAM J. Appl. Math., 1993

The Dynamics of the Theta Method.
SIAM J. Sci. Comput., 1991

Nonlinear Instability in Dissipative Finite Difference Schemes.
SIAM Rev., 1989