TY - JOUR A1 - Lie, Han Cheng A1 - Sullivan, T. J. T1 - Erratum: Equivalence of weak and strong modes of measures on topological vector spaces (2018 Inverse Problems 34 115013) JF - Inverse Problems Y1 - 2018 U6 - https://doi.org/10.1088/1361-6420/aae55b VL - 34 IS - 12 SP - 129601 ER - TY - JOUR A1 - Oates, Chris A1 - Sullivan, T. J. T1 - A modern retrospective on probabilistic numerics JF - Statistics and Computing N2 - This article attempts to place the emergence of probabilistic numerics as a mathematical-statistical research field within its historical context and to explore how its gradual development can be related to modern formal treatments and applications. We highlight in particular the parallel contributions of Sul'din and Larkin in the 1960s and how their pioneering early ideas have reached a degree of maturity in the intervening period, mediated by paradigms such as average-case analysis and information-based complexity. We provide a subjective assessment of the state of research in probabilistic numerics and highlight some difficulties to be addressed by future works. Y1 - 2019 U6 - https://doi.org/10.1007/s11222-019-09902-z VL - 29 IS - 6 SP - 1335 EP - 1351 ER - TY - JOUR A1 - Kersting, Hans A1 - Sullivan, T. J. A1 - Hennig, Philipp T1 - Convergence rates of Gaussian ODE filters JF - Statistics and Computing Y1 - 2020 U6 - https://doi.org/10.1007/s11222-020-09972-4 VL - 30 SP - 1791 EP - 1816 PB - Springer CY - Statistics and Computing ER - TY - JOUR A1 - Lie, Han Cheng A1 - Sullivan, T. J. A1 - Teckentrup, Aretha T1 - Error bounds for some approximate posterior measures in Bayesian inference JF - Numerical Mathematics and Advanced Applications ENUMATH 2019 Y1 - 2020 U6 - https://doi.org/10.1007/978-3-030-55874-1_26 SP - 275 EP - 283 PB - Springer ER - TY - JOUR A1 - Lie, Han Cheng A1 - Sullivan, T. J. T1 - Cameron--Martin theorems for sequences of Cauchy-distributed random variables JF - arXiv N2 - Given a sequence of Cauchy-distributed random variables defined by a sequence of location parameters and a sequence of scale parameters, we consider another sequence of random variables that is obtained by perturbing the location or scale parameter sequences. Using a result of Kakutani on equivalence of infinite product measures, we provide sufficient conditions for the equivalence of laws of the two sequences. Y1 - 2016 SP - 1608.03784 ER - TY - JOUR A1 - Klebanov, Ilja A1 - Schuster, Ingmar A1 - Sullivan, T. J. T1 - A rigorous theory of conditional mean embeddings JF - SIAM Journal on Mathematics of Data Science Y1 - 2020 U6 - https://doi.org/10.1137/19M1305069 VL - 2 IS - 3 SP - 583 EP - 606 ER - TY - JOUR A1 - Girolami, Mark A. A1 - Ipsen, Ilse C. F. A1 - Oates, Chris A1 - Owen, Art B. A1 - Sullivan, T. J. T1 - Editorial: Special edition on probabilistic numerics JF - Statistics and Computing Y1 - 2019 U6 - https://doi.org/doi:10.1007/s11222-019-09892-y VL - 29 IS - 6 SP - 1181 EP - 1183 ER - TY - JOUR A1 - Nava-Yazdani, Esfandiar A1 - Hege, Hans-Christian A1 - Sullivan, T. J. A1 - von Tycowicz, Christoph T1 - Geodesic Analysis in Kendall's Shape Space with Epidemiological Applications JF - Journal of Mathematical Imaging and Vision N2 - We analytically determine Jacobi fields and parallel transports and compute geodesic regression in Kendall’s shape space. Using the derived expressions, we can fully leverage the geometry via Riemannian optimization and thereby reduce the computational expense by several orders of magnitude over common, nonlinear constrained approaches. The methodology is demonstrated by performing a longitudinal statistical analysis of epidemiological shape data. As an example application we have chosen 3D shapes of knee bones, reconstructed from image data of the Osteoarthritis Initiative (OAI). Comparing subject groups with incident and developing osteoarthritis versus normal controls, we find clear differences in the temporal development of femur shapes. This paves the way for early prediction of incident knee osteoarthritis, using geometry data alone. Y1 - 2020 U6 - https://doi.org/10.1007/s10851-020-00945-w VL - 62 IS - 4 SP - 549 EP - 559 ER - TY - JOUR A1 - Klebanov, Ilja A1 - Sprungk, Björn A1 - Sullivan, T. J. T1 - The linear conditional expectation in Hilbert space JF - Bernoulli Y1 - 2021 U6 - https://doi.org/10.3150/20-BEJ1308 VL - 27 IS - 4 SP - 2299 EP - 2299 ER - TY - JOUR A1 - Bonnet, Luc A1 - Akian, Jean-Luc A1 - Savin, Éric A1 - Sullivan, T. J. T1 - Adaptive reconstruction of imperfectly-observed monotone functions, with applications to uncertainty quantification JF - Algorithms N2 - Motivated by the desire to numerically calculate rigorous upper and lower bounds on deviation probabilities over large classes of probability distributions, we present an adaptive algorithm for the reconstruction of increasing real-valued functions. While this problem is similar to the classical statistical problem of isotonic regression, the optimisation setting alters several characteristics of the problem and opens natural algorithmic possibilities. We present our algorithm, establish sufficient conditions for convergence of the reconstruction to the ground truth, and apply the method to synthetic test cases and a real-world example of uncertainty quantification for aerodynamic design. Y1 - 2020 U6 - https://doi.org/10.3390/a13080196 VL - 13 IS - 8 SP - 196 ER -