Andrew M Stuart

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Kody J. H. LawProfessor at the University of Manchester and AI Research Scientist at MetaVerified email at meta.com
G.A. PavliotisDepartment of Mathematics Imperial College LondonVerified email at imperial.ac.uk
Nikola KovachkiCalifornia Institute of TechnologyVerified email at caltech.edu
Kaushik BhattacharyaCalifornia Institute of TechnologyVerified email at caltech.edu
Burigede LiuGranta Design Assistant Professor, University of CambridgeVerified email at cam.ac.uk
Gareth RobertsProfessor of Statistics, University of WarwickVerified email at warwick.ac.uk
Zongyi LiCaltechVerified email at caltech.edu
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Kamyar AzizzadenesheliNvidiaVerified email at nvidia.com
Tapio SchneiderProfessor, California Institute of TechnologyVerified email at caltech.edu
Jonathan C. MattinglyProfessor of Mathematics and Statistical Science, Duke UniversityVerified email at math.duke.edu
Jochen VossLecturer in Statistics, University of LeedsVerified email at leeds.ac.uk
Natesh S. PillaiHarvard UniversityVerified email at fas.harvard.edu
Alexandros BeskosProfessor in Statistics, UCLVerified email at ucl.ac.uk
Antony R HumphriesMathematics & Statistics, and, Physiology, McGill UniversityVerified email at mcgill.ca
Simon CotterSchool of Mathematics, University of ManchesterVerified email at manchester.ac.uk
Marco IglesiasUniversity of NottinghamVerified email at nottingham.ac.uk
Konstantinos ZygalakisUniversity of EdinburghVerified email at ed.ac.uk
Desmond HighamProfessor of Mathematics, University of EdinburghVerified email at ed.ac.uk
Martin HairerProfessor of Mathematics, Imperial College LondonVerified email at imperial.ac.uk

Andrew M Stuart

Computing + Mathematical Sciences, Caltech

Verified email at caltech.edu - Homepage

Applied and Computational Mathematics Data Assimilation Inverse Problems Stochastic Differential Equations


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Inverse problems: a Bayesian perspective AM Stuart Acta numerica 19, 451-559, 2010	1800	2010
Multiscale methods: averaging and homogenization G Pavliotis, A Stuart Springer Science & Business Media, 2008	1322*	2008
Dynamical systems and numerical analysis A Stuart, AR Humphries Cambridge University Press, 1998	1286	1998
Fourier neural operator for parametric partial differential equations Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ... arXiv preprint arXiv:2010.08895, 2020	1243	2020
Strong convergence of Euler-type methods for nonlinear stochastic differential equations DJ Higham, X Mao, AM Stuart SIAM journal on numerical analysis 40 (3), 1041-1063, 2002	790	2002
Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise JC Mattingly, AM Stuart, DJ Higham Stochastic processes and their applications 101 (2), 185-232, 2002	702	2002
MCMC methods for functions: modifying old algorithms to make them faster SL Cotter, GO Roberts, AM Stuart, D White	658	2013
The Bayesian approach to inverse problems M Dashti, AM Stuart arXiv preprint arXiv:1302.6989, 2013	579	2013
Data assimilation K Law, A Stuart, K Zygalakis Cham, Switzerland: Springer 214, 52, 2015	543	2015
Neural operator: Graph kernel network for partial differential equations A Anandkumar, K Azizzadenesheli, K Bhattacharya, N Kovachki, Z Li, ... ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020	443*	2020
Extracting macroscopic dynamics: model problems and algorithms D Givon, R Kupferman, A Stuart Nonlinearity 17 (6), R55, 2004	429	2004
Optimal tuning of the hybrid Monte Carlo algorithm A Beskos, N Pillai, G Roberts, JM Sanz-Serna, A Stuart	369	2013
Ensemble Kalman methods for inverse problems MA Iglesias, KJH Law, AM Stuart Inverse Problems 29 (4), 045001, 2013	354	2013
The global dynamics of discrete semilinear parabolic equations CM Elliott, AM Stuart SIAM journal on numerical analysis 30 (6), 1622-1663, 1993	353	1993
Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs. NB Kovachki, Z Li, B Liu, K Azizzadenesheli, K Bhattacharya, AM Stuart, ... J. Mach. Learn. Res. 24 (89), 1-97, 2023	329*	2023
Earth system modeling 2.0: A blueprint for models that learn from observations and targeted high‐resolution simulations T Schneider, S Lan, A Stuart, J Teixeira Geophysical Research Letters 44 (24), 12,396-12,417, 2017	315	2017
A first course in continuum mechanics O Gonzalez, AM Stuart Cambridge University Press, 2008	285	2008
A model mechanism for the chemotactic response of endothelial cells to tumour angiogenesis factor MAJ Chaplain, AM Stuart Mathematical Medicine and Biology: A Journal of the IMA 10 (3), 149-168, 1993	259	1993
MCMC methods for diffusion bridges A Beskos, G Roberts, A Stuart, J Voss Stochastics and Dynamics 8 (03), 319-350, 2008	247	2008
Model reduction and neural networks for parametric PDEs K Bhattacharya, B Hosseini, NB Kovachki, AM Stuart The SMAI journal of computational mathematics 7, 121-157, 2021	243	2021

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