Andrew M. Stuart
Orcid: 0000-0001-9091-7266Affiliations:
- California Institute of Technology, Pasadena, CA, USA
- University of Warwick, Department of Mathematics, Coventry, UK (former)
According to our database1,
Andrew M. Stuart
authored at least 99 papers
between 1989 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on zbmath.org
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on orcid.org
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on id.loc.gov
On csauthors.net:
Bibliography
2024
2023
Multiscale Model. Simul., June, 2023
SIAM/ASA J. Uncertain. Quantification, June, 2023
Found. Comput. Math., February, 2023
J. Mach. Learn. Res., 2023
Modeling groundwater levels in California's Central Valley by hierarchical Gaussian process and neural network regression.
CoRR, 2023
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance.
CoRR, 2023
Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures.
CoRR, 2023
2022
SIAM J. Appl. Dyn. Syst., 2022
SIAM J. Appl. Dyn. Syst., 2022
Ensemble Kalman inversion for sparse learning of dynamical systems from time-averaged data.
J. Comput. Phys., 2022
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
2021
SIAM J. Sci. Comput., 2021
Consistency of empirical Bayes and kernel flow for hierarchical parameter estimation.
Math. Comput., 2021
CoRR, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
SIAM J. Sci. Comput., 2020
SIAM J. Appl. Dyn. Syst., 2020
Multiscale Model. Simul., 2020
Consistency of Semi-Supervised Learning Algorithms on Graphs: Probit and One-Hot Methods.
J. Mach. Learn. Res., 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Lessons learned from assimilating knowledge into machine learning to forecast and control glucose in a critical care setting.
Proceedings of the AMIA 2020, 2020
2019
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
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
2018
Posterior consistency for Gaussian process approximations of Bayesian posterior distributions.
Math. Comput., 2018
SIAM/ASA J. Uncertain. Quantification, 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
CoRR, 2018
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
2017
SIAM J. Numer. Anal., 2017
SIAM J. Math. Anal., 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
SIAM/ASA J. Uncertain. Quantification, 2017
CoRR, 2017
Proceedings of the AMIA 2017, 2017
2016
Using data assimilation to forecast post-meal glucose for patients with type 2 diabetes.
Proceedings of the AMIA 2016, 2016
2015
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
Stat. Comput., 2015
Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems.
SIAM/ASA J. Uncertain. Quantification, 2015
J. Nonlinear Sci., 2015
2014
SIAM/ASA J. Uncertain. Quantification, 2014
2011
SIAM J. Numer. Anal., 2011
2010
Convergence of Numerical Time-Averaging and Stationary Measures via Poisson Equations.
SIAM J. Numer. Anal., 2010
2009
J. Comput. Phys., 2009
2006
SIAM J. Appl. Dyn. Syst., 2006
2005
Analysis of White Noise Limits for Stochastic Systems with Two Fast Relaxation Times.
Multiscale Model. Simul., 2005
2003
Multiscale Model. Simul., 2003
Exponential Mean-Square Stability of Numerical Solutions to Stochastic Differential Equations.
LMS J. Comput. Math., 2003
2002
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
2001
2000
A Perturbation Theory for Ergodic Markov Chains and Application to Numerical Approximations.
SIAM J. Numer. Anal., 2000
1998
SIAM J. Sci. Comput., 1998
On the Solution of Convection-Diffusion Boundary Value Problems Using Equidistributed Grids.
SIAM J. Sci. Comput., 1998
1997
Probabilistic and deterministic convergence proofs for software for initial value problems.
Numer. Algorithms, 1997
1994
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
1993
SIAM J. Appl. Math., 1993
The Numerical Computation of Heteroclinic Connections in Systems of Gradient Partial Differential Equations.
SIAM J. Appl. Math., 1993
1991
1989