Andrew M. Stuart

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

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2021

Calibrate, emulate, sample.

Emmet Cleary, Alfredo Garbuno-Inigo, Shiwei Lan, Tapio Schneider, Andrew M. Stuart

J. Comput. Phys., 2021

2020

Reconciling Bayesian and Perimeter Regularization for Binary Inversion.

Oliver R. A. Dunbar, Matthew M. Dunlop, Charles M. Elliott, Viet Ha Hoang, Andrew M. Stuart

SIAM J. Sci. Comput., 2020

Tikhonov Regularization within Ensemble Kalman Inversion.

Neil K. Chada, Andrew M. Stuart, Xin T. Tong

SIAM J. Numer. Anal., 2020

Inverse Optimal Transport.

Andrew M. Stuart, Marie-Therese Wolfram

SIAM J. Appl. Math., 2020

Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler.

Alfredo Garbuno-Inigo, Franca Hoffmann, Wuchen Li, Andrew M. Stuart

SIAM J. Appl. Dyn. Syst., 2020

Consistency of Semi-Supervised Learning Algorithms on Graphs: Probit and One-Hot Methods.

Franca Hoffmann, Bamdad Hosseini, Zhi Ren, Andrew M. Stuart

J. Mach. Learn. Res., 2020

Fourier Neural Operator for Parametric Partial Differential Equations.

Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

CoRR, 2020

Drift Estimation of Multiscale Diffusions Based on Filtered Data.

Assyr Abdulle, Giacomo Garegnani, Grigorios A. Pavliotis, Andrew M. Stuart, Andrea Zanoni

CoRR, 2020

Posterior Consistency of Semi-Supervised Regression on Graphs.

Andrea L. Bertozzi, Bamdad Hosseini, Hao Li, Kevin Miller, Andrew M. Stuart

CoRR, 2020

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

Yifan Chen, Houman Owhadi, Andrew M. Stuart

CoRR, 2020

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

Nicholas H. Nelsen, Andrew M. Stuart

CoRR, 2020

Model Reduction and Neural Networks for Parametric PDEs.

Kaushik Bhattacharya, Bamdad Hosseini, Nikola B. Kovachki, Andrew M. Stuart

CoRR, 2020

Neural Operator: Graph Kernel Network for Partial Differential Equations.

Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar

CoRR, 2020

Multipole Graph Neural Operator for Parametric Partial Differential Equations.

Zongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Andrew M. Stuart, Kaushik Bhattacharya, Anima Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Parameter Estimation for Macroscopic Pedestrian Dynamics Models from Microscopic Data.

Susana N. Gomes, Andrew M. Stuart, Marie-Therese Wolfram

SIAM J. Appl. Math., 2019

Strong convergence rates of probabilistic integrators for ordinary differential equations.

Han Cheng Lie, Andrew M. Stuart, Timothy John Sullivan

Stat. Comput., 2019

Analysis Of Momentum Methods.

Nikola B. Kovachki, Andrew M. Stuart

CoRR, 2019

Uncertainty quantification for semi-supervised multi-class classification in image processing and ego-motion analysis of body-worn videos.

Yiling Qiao, Chang Shi, Chenjian Wang, Hao Li, Matt Haberland, Xiyang Luo, Andrew M. Stuart, Andrea L. Bertozzi

Proceedings of the Image Processing: Algorithms and Systems XVII, 2019

2018

Posterior consistency for Gaussian process approximations of Bayesian posterior distributions.

Andrew M. Stuart, Aretha L. Teckentrup

Math. Comput., 2018

Uncertainty Quantification in Graph-Based Classification of High Dimensional Data.

Andrea L. Bertozzi, Xiyang Luo, Andrew M. Stuart, Konstantinos C. Zygalakis

SIAM/ASA J. Uncertain. Quantification, 2018

How Deep Are Deep Gaussian Processes?

Matthew M. Dunlop, Mark A. Girolami, Andrew M. Stuart, Aretha L. Teckentrup

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.

David J. Albers, Matthew E. Levine, Andrew M. Stuart, Lena Mamykina, Bruce J. Gluckman, George Hripcsak

J. Am. Medical Informatics Assoc., 2018

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

Nikola B. Kovachki, Andrew M. Stuart

CoRR, 2018

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

Matthew M. Dunlop, Dejan Slepcev, Andrew M. Stuart, Matthew Thorpe

CoRR, 2018

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

David J. Albers, Matthew E. Levine, Andrew M. Stuart, Jan Claassen, Bruce J. Gluckman, George Hripcsak

Proceedings of the AMIA 2018, 2018

2017

Analysis of the Ensemble Kalman Filter for Inverse Problems.

Claudia Schillings, Andrew M. Stuart

SIAM J. Numer. Anal., 2017

Gaussian Approximations for Transition Paths in Brownian Dynamics.

Yulong Lu, Andrew M. Stuart, Hendrik Weber

SIAM J. Math. Anal., 2017

Hierarchical Bayesian level set inversion.

Matthew M. Dunlop, Marco A. Iglesias, Andrew M. Stuart

Stat. Comput., 2017

Statistical analysis of differential equations: introducing probability measures on numerical solutions.

Patrick R. Conrad, Mark A. Girolami, Simo Särkkä, Andrew M. Stuart, Konstantinos Zygalakis

Stat. Comput., 2017

Quasi-Monte Carlo and Multilevel Monte Carlo Methods for Computing Posterior Expectations in Elliptic Inverse Problems.

Robert Scheichl, Andrew M. Stuart, Aretha L. Teckentrup

SIAM/ASA J. Uncertain. Quantification, 2017

Gaussian Approximations for Probability Measures on R^d.

Yulong Lu, Andrew M. Stuart, Hendrik Weber

SIAM/ASA J. Uncertain. Quantification, 2017

Geometric MCMC for infinite-dimensional inverse problems.

Alexandros Beskos, Mark A. Girolami, Shiwei Lan, Patrick E. Farrell, Andrew M. Stuart

J. Comput. Phys., 2017

Uncertainty Quantification in the Classification of High Dimensional Data.

Andrea L. Bertozzi, Xiyang Luo, Andrew M. Stuart, Konstantinos C. Zygalakis

CoRR, 2017

Why predicting postprandial glucose using self-monitoring data is difficult.

David J. Albers, Matthew E. Levine, Andrew M. Stuart, Bruce J. Gluckman, George Hripcsak

Proceedings of the AMIA 2017, 2017

2016

Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes.

David J. Albers, Matthew E. Levine, Andrew M. Stuart, George Hripcsak, Lena Mamykina

Proceedings of the AMIA 2016, 2016

2015

Algorithms for Kullback-Leibler Approximation of Probability Measures in Infinite Dimensions.

F. J. Pinski, Gideon Simpson, Andrew M. Stuart, H. Weber

SIAM J. Sci. Comput., 2015

Kullback-Leibler Approximation for Probability Measures on Infinite Dimensional Spaces.

F. J. Pinski, Gideon Simpson, Andrew M. Stuart, H. Weber

SIAM J. Math. Anal., 2015

Sequential Monte Carlo methods for Bayesian elliptic inverse problems.

Alexandros Beskos, Ajay Jasra, Ege A. Muzaffer, Andrew M. Stuart

Stat. Comput., 2015

Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems.

Daniel Sanz-Alonso, Andrew M. Stuart

SIAM/ASA J. Uncertain. Quantification, 2015

A Multiscale Analysis of Diffusions on Rapidly Varying Surfaces.

A. B. Duncan, Charles M. Elliott, Grigorios A. Pavliotis, Andrew M. Stuart

J. Nonlinear Sci., 2015

2014

Analysis of the Gibbs Sampler for Hierarchical Inverse Problems.

Sergios Agapiou, Johnathan M. Bardsley, Omiros Papaspiliopoulos, Andrew M. Stuart

SIAM/ASA J. Uncertain. Quantification, 2014

2011

Uncertainty Quantification and Weak Approximation of an Elliptic Inverse Problem.

M. Dashti, Andrew M. Stuart

SIAM J. Numer. Anal., 2011

Evaluating Data Assimilation Algorithms

Kody J. H. Law, Andrew M. Stuart

CoRR, 2011

2010

Convergence of Numerical Time-Averaging and Stationary Measures via Poisson Equations.

Jonathan C. Mattingly, Andrew M. Stuart, Michael V. Tretyakov

SIAM J. Numer. Anal., 2010

Approximation of Bayesian Inverse Problems for PDEs.

S. L. Cotter, M. Dashti, Andrew M. Stuart

SIAM J. Numer. Anal., 2010

Inverse problems: A Bayesian perspective.

Andrew M. Stuart

Acta Numer., 2010

2009

Remarks on Drift Estimation for Diffusion Processes.

Yvo Pokern, Andrew M. Stuart, Eric Vanden-Eijnden

Multiscale Model. Simul., 2009

Calculating effective diffusivities in the limit of vanishing molecular diffusion.

Grigorios A. Pavliotis, Andrew M. Stuart, Konstantinos C. Zygalakis

J. Comput. Phys., 2009

2006

The Moment Map: Nonlinear Dynamics of Density Evolution via a Few Moments.

Dwight Barkley, Ioannis G. Kevrekidis, Andrew M. Stuart

SIAM J. Appl. Dyn. Syst., 2006

2005

Analysis of White Noise Limits for Stochastic Systems with Two Fast Relaxation Times.

Grigorios A. Pavliotis, Andrew M. Stuart

Multiscale Model. Simul., 2005

2003

White Noise Limits for Inertial Particles in a Random Field.

Grigorios A. Pavliotis, Andrew M. Stuart

Multiscale Model. Simul., 2003

2002

Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations.

Desmond J. Higham, Xuerong Mao, Andrew M. Stuart

SIAM J. Numer. Anal., 2002

The dynamical behavior of the discontinuous Galerkin method and related difference schemes.

Donald J. Estep, Andrew M. Stuart

Math. Comput., 2002

2001

Stiff Oscillatory Systems, Delta Jumps and White Noise.

Begoña Cano, Andrew M. Stuart, Endre Süli, J. O. Warren

Found. Comput. Math., 2001

2000

A Perturbation Theory for Ergodic Markov Chains and Application to Numerical Approximations.

Tony Shardlow, Andrew M. Stuart

SIAM J. Numer. Anal., 2000

1998

Space-Time Continuous Analysis of Waveform Relaxation for the Heat Equation.

Martin J. Gander, Andrew M. Stuart

SIAM J. Sci. Comput., 1998

On the Solution of Convection-Diffusion Boundary Value Problems Using Equidistributed Grids.

Chris J. Budd, George P. Koomullil, Andrew M. Stuart

SIAM J. Sci. Comput., 1998

1997

Probabilistic and deterministic convergence proofs for software for initial value problems.

Andrew M. Stuart

Numer. Algorithms, 1997

Waveform relaxation as a dynamical system.

Morten Bjørhus, Andrew M. Stuart

Math. Comput., 1997

1994

Model Problems in Numerical Stability Theory for Initial Value Problems.

Andrew M. Stuart, A. R. Humphries

SIAM Rev., 1994

Blow-up in a System of Partial Differential Equations with Conserved First Integral. Part II: Problems with Convection.

Chris J. Budd, J. William Dold, Andrew M. Stuart

SIAM J. Appl. Math., 1994

1993

Blowup in a Partial Differential Equation with Conserved First Integral.

Chris J. Budd, J. William Dold, Andrew M. Stuart

SIAM J. Appl. Math., 1993

The Numerical Computation of Heteroclinic Connections in Systems of Gradient Partial Differential Equations.

Fengshan Bai, Alastair Spence, Andrew M. Stuart

SIAM J. Appl. Math., 1993

1991

The Dynamics of the Theta Method.

Andrew M. Stuart, A. T. Peplow

SIAM J. Sci. Comput., 1991

1989

Nonlinear Instability in Dissipative Finite Difference Schemes.

Andrew M. Stuart

SIAM Rev., 1989