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ORCIDTimothy John Sullivan
Person information
- affiliation: Free University of Berlin, Germany
- affiliation: Zuse Institute Berlin, Germany
Other persons with the same name
- Tim Sullivan — disambiguation page
- Tim Sullivan 0002 — Hewlett-Packard Labs., Palo Alto, CA, USA
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2020 – today
- 2024
[i23]Justin Bunker, Mark Girolami, Hefin Lambley, Andrew M. Stuart, Tim Sullivan:
Autoencoders in Function Space. CoRR abs/2408.01362 (2024)- 2023
- [j20]Hefin Lambley
, Timothy John Sullivan:
An Order-Theoretic Perspective on Modes and Maximum A Posteriori Estimation in Bayesian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 11(4): 1195-1224 (2023) - [j19]Kamran Pentland, Massimiliano Tamborrino, Timothy John Sullivan, James Buchanan, Lynton C. Appel:
GParareal: a time-parallel ODE solver using Gaussian process emulation. Stat. Comput. 33(1): 23 (2023) - [j18]Kamran Pentland, Massimiliano Tamborrino, Timothy John Sullivan:
Error Bound Analysis of the Stochastic Parareal Algorithm. SIAM J. Sci. Comput. 45(5): 2657- (2023) - [i22]Ilja Klebanov, Timothy John Sullivan:
Transporting Higher-Order Quadrature Rules: Quasi-Monte Carlo Points and Sparse Grids for Mixture Distributions. CoRR abs/2308.10081 (2023) - 2022
- [j17]Jon Cockayne, Matthew M. Graham, Chris J. Oates, Timothy John Sullivan, Onur Teymur:
Testing Whether a Learning Procedure is Calibrated. J. Mach. Learn. Res. 23: 203:1-203:36 (2022) - [i21]Kamran Pentland, Massimiliano Tamborrino, Timothy John Sullivan, James Buchanan, Lynton C. Appel:
GParareal: A time-parallel ODE solver using Gaussian process emulation. CoRR abs/2201.13418 (2022) - [i20]Kamran Pentland, Massimiliano Tamborrino, Timothy John Sullivan:
Error bound analysis of the stochastic parareal algorithm. CoRR abs/2211.05496 (2022) - 2021
- [j16]Florian Schäfer, Timothy John Sullivan, Houman Owhadi:
Compression, Inversion, and Approximate PCA of Dense Kernel Matrices at Near-Linear Computational Complexity. Multiscale Model. Simul. 19(2): 688-730 (2021) - [j15]Junyang Wang, Jon Cockayne, Oksana A. Chkrebtii, Timothy John Sullivan, Chris J. Oates:
Bayesian numerical methods for nonlinear partial differential equations. Stat. Comput. 31(5): 55 (2021) - [i19]Han Cheng Lie, Martin Stahn, Timothy John Sullivan:
Randomised one-step time integration methods for deterministic operator differential equations. CoRR abs/2103.16506 (2021) - [i18]Junyang Wang, Jon Cockayne, Oksana A. Chkrebtii, Timothy John Sullivan, Chris J. Oates:
Bayesian Numerical Methods for Nonlinear Partial Differential Equations. CoRR abs/2104.12587 (2021) - [i17]Birzhan Ayanbayev, Ilja Klebanov, Han Cheng Lie, Timothy John Sullivan:
Γ-convergence of Onsager-Machlup functionals. Part I: With applications to maximum a posteriori estimation in Bayesian inverse problems. CoRR abs/2108.04597 (2021) - [i16]Birzhan Ayanbayev, Ilja Klebanov, Han Cheng Lie, Timothy John Sullivan:
Γ-convergence of Onsager-Machlup functionals. Part II: Infinite product measures on Banach spaces. CoRR abs/2108.04598 (2021) - [i15]Han Cheng Lie, Daniel Rudolf, Björn Sprungk, Timothy John Sullivan:
Dimension-independent Markov chain Monte Carlo on the sphere. CoRR abs/2112.12185 (2021) - [i14]Philipp Hennig, Ilse C. F. Ipsen, Maren Mahsereci, Tim Sullivan:
Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432). Dagstuhl Reports 11(9): 102-119 (2021) - 2020
- [j14]Luc Bonnet, Jean-Luc Akian, Éric Savin, Timothy John Sullivan:
Adaptive Reconstruction of Imperfectly Observed Monotone Functions, with Applications to Uncertainty Quantification. Algorithms 13(8): 196 (2020) - [j13]Esfandiar Nava-Yazdani, Hans-Christian Hege, Timothy John Sullivan, Christoph von Tycowicz:
Geodesic Analysis in Kendall's Shape Space with Epidemiological Applications. J. Math. Imaging Vis. 62(4): 549-559 (2020) - [j12]Hans Kersting, Timothy John Sullivan, Philipp Hennig:
Convergence rates of Gaussian ODE filters. Stat. Comput. 30(6): 1791-1816 (2020) - [j11]Ilja Klebanov, Ingmar Schuster, Timothy John Sullivan:
A Rigorous Theory of Conditional Mean Embeddings. SIAM J. Math. Data Sci. 2(3): 583-606 (2020) - [i13]Luc Bonnet, Jean-Luc Akian, Éric Savin, Timothy John Sullivan:
Adaptive reconstruction of imperfectly-observed monotone functions, with applications to uncertainty quantification. CoRR abs/2007.05236 (2020) - [i12]Mike McKerns, Francis J. Alexander, Kyle S. Hickmann, Timothy John Sullivan, Diane E. Vaughan:
Optimal Bounds on Nonlinear Partial Differential Equations in Model Certification, Validation, and Experimental Design. CoRR abs/2009.06626 (2020)
2010 – 2019
- 2019
- [j10]Mark A. Girolami, Ilse C. F. Ipsen, Chris J. Oates, Art B. Owen, Timothy John Sullivan:
Editorial: special edition on probabilistic numerics. Stat. Comput. 29(6): 1181-1183 (2019) - [j9]Han Cheng Lie, Andrew M. Stuart, Timothy John Sullivan:
Strong convergence rates of probabilistic integrators for ordinary differential equations. Stat. Comput. 29(6): 1265-1283 (2019) - [j8]Chris J. Oates, Timothy John Sullivan:
A modern retrospective on probabilistic numerics. Stat. Comput. 29(6): 1335-1351 (2019) - [j7]Jon Cockayne, Chris J. Oates, Timothy John Sullivan, Mark A. Girolami:
Bayesian Probabilistic Numerical Methods. SIAM Rev. 61(4): 756-789 (2019) - [c2]Han Cheng Lie, Timothy John Sullivan, Aretha L. Teckentrup:
Error Bounds for Some Approximate Posterior Measures in Bayesian Inference. ENUMATH 2019: 275-283 - [i11]Timothy John Sullivan:
Comments on the article "A Bayesian conjugate gradient method". CoRR abs/1906.10240 (2019) - [i10]Han Cheng Lie, Timothy John Sullivan, Aretha L. Teckentrup:
Error bounds for some approximate posterior measures in Bayesian inference. CoRR abs/1911.05669 (2019) - 2018
- [j6]Han Cheng Lie, Timothy John Sullivan, Aretha L. Teckentrup:
Random Forward Models and Log-Likelihoods in Bayesian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 6(4): 1600-1629 (2018) - [c1]Onur Teymur, Han Cheng Lie, Tim Sullivan, Ben Calderhead:
Implicit Probabilistic Integrators for ODEs. NeurIPS 2018: 7255-7264 - [i9]Hans Kersting, Timothy John Sullivan, Philipp Hennig:
Convergence Rates of Gaussian ODE Filters. CoRR abs/1807.09737 (2018) - 2017
- [i8]Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami:
Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems. CoRR abs/1701.04006 (2017) - [i7]Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami:
Bayesian Probabilistic Numerical Methods. CoRR abs/1702.03673 (2017) - [i6]Florian Schäfer, Timothy John Sullivan, Houman Owhadi:
Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity. CoRR abs/1706.02205 (2017) - [i5]Han Cheng Lie, Timothy John Sullivan, Aretha L. Teckentrup:
Random forward models and log-likelihoods in Bayesian inverse problems. CoRR abs/1712.05717 (2017) - 2016
- [i4]Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami:
Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems. CoRR abs/1605.07811 (2016) - 2015
- [j5]Houman Owhadi, Clint Scovel, Timothy John Sullivan:
On the Brittleness of Bayesian Inference. SIAM Rev. 57(4): 566-582 (2015) - 2013
- [j4]Houman Owhadi, Clint Scovel, Timothy John Sullivan, Mike McKerns, Michael Ortiz:
Optimal Uncertainty Quantification. SIAM Rev. 55(2): 271-345 (2013) - 2012
- [i3]Mike McKerns, Houman Owhadi, Clint Scovel, Timothy John Sullivan, Michael Ortiz:
The Optimal Uncertainty Algorithm in the Mystic Framework. CoRR abs/1202.1055 (2012) - [i2]Timothy John Sullivan, Mike McKerns, Dominik Meyer, Florian Theil, Houman Owhadi, Michael Ortiz:
Optimal uncertainty quantification for legacy data observations of Lipschitz functions. CoRR abs/1202.1928 (2012) - 2010
- [i1]Houman Owhadi, Clint Scovel, Timothy John Sullivan, Mike McKerns, Michael Ortiz:
Optimal Uncertainty Quantification. CoRR abs/1009.0679 (2010)
2000 – 2009
- 2005
- [j3]Michael C. Saunders, Timothy John Sullivan, B. L. Nash, K. A. Tonnessen, B. J. Miller:
A knowledge-based approach for classifying lake water chemistry. Knowl. Based Syst. 18(1): 47-54 (2005) - [j2]Timothy John Sullivan, Michael C. Saunders, K. A. Tonnessen, B. L. Nash, B. J. Miller:
Application of a regionalized knowledge-based model for classifying the impacts of nitrogen, sulfur, and organic acids on lakewater chemistry. Knowl. Based Syst. 18(1): 55-68 (2005) - 2004
- [j1]Timothy John Sullivan, W. L. Perry:
Identifying indicators of chemical, biological, radiological, and nuclear (CBRN) weapons development activity in sub-national terrorist groups. J. Oper. Res. Soc. 55(4): 361-374 (2004)
Coauthor Index
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