T. J. Sullivan

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Houman OwhadiProfessor of Applied and Computational Mathematics and Control and Dynamical Systems, CaliforniaVerified email at caltech.edu
Michael OrtizCaltech AND Brown UniversityVerified email at caltech.edu
Chris. J. OatesNewcastle UniversityVerified email at ncl.ac.uk
Han Cheng LieProfessor (W1) for Uncertainty Quantification, Universität PotsdamVerified email at uni-potsdam.de
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Bo LiPeking UniversityVerified email at pku.edu.cn
Ilja KlebanovPostdoc, Free University of BerlinVerified email at zedat.fu-berlin.de
Alta FangR&D Development Engineer, BIOVIAVerified email at 3ds.com
Onur TeymurUniversity of KentVerified email at kent.ac.uk
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Florian SchaeferGeorgia TechVerified email at cc.gatech.edu
Aretha L TeckentrupReader in Mathematics of Data Science, University of EdinburghVerified email at ed.ac.uk
Ufuk TopcuThe University of Texas at AustinVerified email at utexas.edu
Hans-Christian HegeZuse Institute Berlin (ZIB)Verified email at zib.de
Christoph von TycowiczHead of Research Group, Zuse Institute BerlinVerified email at zib.de
Marisol KoslowskiPurdueVerified email at purdue.edu
Hans KerstingResearch Scientist, Yahoo ResearchVerified email at yahooinc.com
Vinod K TewaryNational Institute of Standards & Technology (NIST)Verified email at nist.gov
Lauren RastThe University of Alabama at BirminghamVerified email at uab.edu
Ares RosakisVon Karman Professor of Aeronautics and Professor of Mechanical Engineering, California Institute of TechnologyVerified email at caltech.edu

T. J. Sullivan

University of Warwick and Alan Turing Institute

Verified email at warwick.ac.uk - Homepage

Applied Mathematics Applied Probability Uncertainty Quantification Inverse Problems Probabilistic Numerics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Introduction to Uncertainty Quantification TJ Sullivan Texts in Applied Mathematics 63, Springer, 2015	595	2015
Building a Framework for Predictive Science M McKerns, L Strand, TJ Sullivan, A Fang, MAG Aivazis Proceedings of the 10th Python in Science Conference (SciPy 2011), June 2011 …, 2011	168	2011
Optimal Uncertainty Quantification H Owhadi, C Scovel, TJ Sullivan, M McKerns, M Ortiz SIAM Review 55 (2), 271-345, 2013	161	2013
Bayesian probabilistic numerical methods J Cockayne, CJ Oates, TJ Sullivan, M Girolami SIAM Review 61 (4), 756-789, 2019	140	2019
On the Brittleness of Bayesian inference H Owhadi, C Scovel, TJ Sullivan SIAM Review 57 (4), 566-582, 2015	72	2015
Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity F Schäfer, TJ Sullivan, H Owhadi Multiscale Modeling & Simulation 19 (2), 688-730, 2021	71	2021
A Modern Retrospective on Probabilistic Numerics CJ Oates, TJ Sullivan Statistics and Computing 29 (6), 1335-1351, 2019	63	2019
Brittleness of Bayesian inference under finite information in a continuous world H Owhadi, C Scovel, TJ Sullivan Electronic Journal of Statistics 9 (1), 1-79, 2015	60	2015
Probabilistic numerical methods for PDE-constrained Bayesian inverse problems J Cockayne, C Oates, TJ Sullivan, M Girolami Proceedings of the 36th International Workshop on Bayesian Inference and …, 2017	35	2017
Well-posed Bayesian inverse problems and heavy-tailed stable quasi-Banach space priors TJ Sullivan Inverse Problems and Imaging 11 (5), 857–874, 2017	35	2017
Convergence rates of Gaussian ODE filters H Kersting, TJ Sullivan, P Hennig Statistics and Computing 30 (6), 1791-1816, 2020	32	2020
Probabilistic meshless methods for partial differential equations and Bayesian inverse problems J Cockayne, C Oates, TJ Sullivan, M Girolami arXiv preprint arXiv:1605.07811, 2016	31	2016
Stratified graphene/noble metal systems for low-loss plasmonics applications L Rast, TJ Sullivan, VK Tewary Physical Review D 87 (4), 045428, 2013	31	2013
Rigorous Model-Based Uncertainty Quantification with Application to Terminal Ballistics. Part I: Systems with Controllable Inputs and Small Scatter AA Kidane, A Lashgari, B Li, M McKerns, M Ortiz, H Owhadi, ... Journal of the Mechanics and Physics of Solids 60 (5), 983-1001, 2012	31	2012
A rigorous theory of conditional mean embeddings I Klebanov, I Schuster, TJ Sullivan SIAM Journal on Mathematics of Data Science 2 (3), 583–606, 2020	29	2020
Strong convergence rates of probabilistic integrators for ordinary differential equations HC Lie, AM Stuart, TJ Sullivan Statistics and Computing 29 (6), 1265-1283, 2019	29	2019
Rigorous Model-Based Uncertainty Quantification with Application to Terminal Ballistics. Part II: Systems with Uncontrollable Inputs and Large Scatter M Adams, A Lashgari, B Li, M McKerns, JM Mihaly, M Ortiz, H Owhadi, ... Journal of the Mechanics and Physics of Solids 60 (5), 1002, 2012	29	2012
Implicit probabilistic integrators for ODEs O Teymur, HC Lie, TJ Sullivan, B Calderhead Advances in Neural Information Processing Systems 31 (NIPS 2018), 2018	27	2018
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	24	2018
Optimal uncertainty quantification with model uncertainty and legacy data P Kamga, B Li, M McKerns, LH Nguyen, M Ortiz, H Owhadi, TJ Sullivan Journal of the Mechanics and Physics of Solids 72, 1-19, 2014	20	2014

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