Aretha L Teckentrup

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Robert ScheichlHeidelberg UniversityVerified email at uni-heidelberg.de
Chris KetelsenR&D Scientist, DigitalGlobeVerified email at digitalglobe.com
Michael B. GilesProfessor of Scientific Computing, University of OxfordVerified email at maths.ox.ac.uk
Andrew M StuartComputing + Mathematical Sciences, CaltechVerified email at caltech.edu
K Andrew CliffeSchool of Mathematical Sciences, University of NottinghamVerified email at nottingham.ac.uk
Max GunzburgerProfessor, Florida State UniversityVerified email at fsu.edu
Tim DodwellCo founder & CTO at digiLab, Professor at University ExeterVerified email at digilab.co.uk
Clayton WebsterUniversity of Texas at AustinVerified email at utexas.edu
Peter JantschWheaton CollegeVerified email at wheaton.edu
Elisabeth UllmannTechnical University of MunichVerified email at ma.tum.de
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Matthew DunlopCourant Institute, New York UniversityVerified email at nyu.edu
Han Cheng LieProfessor (W1) for Uncertainty Quantification, Universität PotsdamVerified email at uni-potsdam.de
T. J. SullivanUniversity of Warwick and Alan Turing InstituteVerified email at warwick.ac.uk
Chris. J. OatesNewcastle UniversityVerified email at ncl.ac.uk
Catherine E PowellMathematics, University of ManchesterVerified email at manchester.ac.uk
Abdul-Lateef Haji-AliHeriot-Watt UniversityVerified email at hw.ac.uk
Martin Thomas BrollySchool of Mathematics, University of EdinburghVerified email at ed.ac.uk
Tapio HelinLUT UniversityVerified email at lut.fi
Konstantinos ZygalakisUniversity of EdinburghVerified email at ed.ac.uk

Aretha L Teckentrup

Reader in Mathematics of Data Science, University of Edinburgh

Verified email at ed.ac.uk - Homepage

Uncertainty Quantification Inverse Problems Numerical Analysis


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Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients KA Cliffe, MB Giles, R Scheichl, AL Teckentrup Computing and Visualization in Science 14, 3-15, 2011	599	2011
Finite element error analysis of elliptic PDEs with random coefficients and its application to multilevel Monte Carlo methods J Charrier, R Scheichl, AL Teckentrup SIAM Journal on Numerical Analysis 51 (1), 322-352, 2013	245	2013
Further analysis of multilevel Monte Carlo methods for elliptic PDEs with random coefficients AL Teckentrup, R Scheichl, MB Giles, E Ullmann Numerische Mathematik 125, 569-600, 2013	235	2013
A hierarchical multilevel Markov chain Monte Carlo algorithm with applications to uncertainty quantification in subsurface flow TJ Dodwell, C Ketelsen, R Scheichl, AL Teckentrup SIAM/ASA Journal on Uncertainty Quantification 3 (1), 1075-1108, 2015	161*	2015
A multilevel stochastic collocation method for partial differential equations with random input data AL Teckentrup, P Jantsch, CG Webster, M Gunzburger SIAM/ASA Journal on Uncertainty Quantification 3 (1), 1046-1074, 2015	139	2015
Posterior consistency for Gaussian process approximations of Bayesian posterior distributions A Stuart, A Teckentrup Mathematics of Computation 87 (310), 721-753, 2018	112	2018
How deep are deep Gaussian processes? MM Dunlop, MA Girolami, AM Stuart, AL Teckentrup Journal of Machine Learning Research 19 (54), 1-46, 2018	107	2018
Quasi-Monte Carlo and multilevel Monte Carlo methods for computing posterior expectations in elliptic inverse problems R Scheichl, AM Stuart, AL Teckentrup SIAM/ASA Journal on Uncertainty Quantification 5 (1), 493-518, 2017	61	2017
Convergence of Gaussian process regression with estimated hyper-parameters and applications in Bayesian inverse problems AL Teckentrup SIAM/ASA Journal on Uncertainty Quantification 8 (4), 1310-1337, 2020	38	2020
Multilevel markov chain monte carlo TJ Dodwell, C Ketelsen, R Scheichl, AL Teckentrup Siam Review 61 (3), 509-545, 2019	38	2019
Multilevel Monte Carlo Methods and Uncertainty Quantification AL Teckentrup University of Bath, 2013	26	2013
Random forward models and log-likelihoods in Bayesian inverse problems HC Lie, TJ Sullivan, AL Teckentrup SIAM/ASA Journal on Uncertainty Quantification 6 (4), 1600-1629, 2018	23	2018
Multilevel Monte Carlo methods for highly heterogeneous media AL Teckentrup Proceedings of the 2012 Winter Simulation Conference (WSC), 1-12, 2012	14	2012
Optimal point sets for total degree polynomial interpolation in moderate dimensions M Gunzburger, AL Teckentrup arXiv preprint arXiv:1407.3291, 2014	11	2014
Adaptive multilevel Monte Carlo for probabilities AL Haji-Ali, J Spence, AL Teckentrup SIAM Journal on Numerical Analysis 60 (4), 2125-2149, 2022	6	2022
A locally adaptive Bayesian cubature method M Fisher, C Oates, C Powell, A Teckentrup International Conference on Artificial Intelligence and Statistics, 1265-1275, 2020	3	2020
ERRATUM: A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow TJ Dodwell, C Ketelsen, R Scheichl, AL Teckentrup SIAM/ASA Journal on Uncertainty Quantification 7 (4), 1398-1399, 2019	3	2019
Improved multilevel Monte Carlo methods for finite volume discretisations of darcy flow in randomly layered media M Park, A Teckentrup arXiv preprint arXiv:1506.04694, 2015	3	2015
Error bounds for some approximate posterior measures in Bayesian inference HC Lie, TJ Sullivan, A Teckentrup Numerical Mathematics and Advanced Applications ENUMATH 2019: European …, 2020	2	2020
Mathematical Foundations for Data Analysis. By Jeff M. Phillips. AL TECKENTRUP SIAM Review Vol. 65, Issue 1 (March 2023) 65 (1), 327, 2023		2023

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