Tim Sullivan

Junior Professor in Applied Mathematics:
Risk and Uncertainty Quantification

Well-posed Bayesian inverse problems and heavy-tailed stable Banach space priors

Preprint: Bayesian inversion with heavy-tailed stable priors

Just uploaded to the arXiv: “Well-posed Bayesian inverse problems and heavy-tailed stable Banach space priors”. This article builds on the function-space formulation of Bayesian inverse problems advocated by Stuart et al. to allow the prior to be heavy-tailed: not only may it not be exponentially integrable, as is the case for a Gaussian or Besov measure, it might not even have a well-defined mean, as in the case of the famous Cauchy distribution on \(\mathbb{R}\).

Abstract. This article extends the framework of Bayesian inverse problems in infinite-dimensional parameter spaces, as advocated by Stuart (Acta Numer. 19:451–559, 2010) and others, to the case of a heavy-tailed prior measure in the family of stable distributions, such as an infinite-dimensional Cauchy distribution, for which polynomial moments are infinite or undefined. It is shown that analogues of the Karhunen–Loève expansion for square-integrable random variables can be used to sample such measures. Furthermore, under weaker regularity assumptions than those used to date, the Bayesian posterior measure is shown to depend Lipschitz continuously in the Hellinger metric upon perturbations of the misfit function and observed data.

Published on Friday 20 May 2016 at 09:00 UTC #publication #preprint #inverse-problems

Zuse 75

The Digital Future: 75th Anniversary of the Zuse Z3

11 May 2016 marks the seventy-fifth anniversary of the unveiling of Konrad Zuse's Z3 computer. The Z3 was the world's first working programmable, fully automatic digital computer.

In celebration of this landmark achievement in computational science, the Zuse Institute, the Berlin–Brandenburg Academy of Sciences, and Der Tagesspiegel are organising a conference on “The Digital Future: 75 Years Zuse Z3 and the Digital Revolution”. For further information, see www.zib.de/zuse75.

Published on Monday 2 May 2016 at 11:00 UTC #event

Steven Niederer

UQ Talks: Steven Niederer

This week Steven Niederer (King's College London) will talk about “Linking physiology and cardiology through mathematical models”

Time and Place. Thursday 28 April 2016, 11:00–12:00, Room 4027 of the Zuse Institute Berlin, Takustraße 7, 14195 Berlin

Abstract. Much effort has gone into the analysis of cardiac function using mathematical and computational models. To fully realise the potential of these studies requires the translation of these models into clinical applications to aid in diagnosis and clinical planning.

To achieve this goal requires the integration of multiple disparate clinical data sets into a common modelling framework. To this end we have developed a coupled electro-mechanics model of the human heart. This model combines patient specific anatomical geometry, active contraction, electrophysiology, tissue heterogeneities and boundary conditions fitted to comprehensive imaging and catheter clinical measurements.

This multi-scale computational model allows us to link sub cellular mechanisms to whole organ function. This provides a novel tool to determine the mechanisms that underpin treatment out comes and offers the ability to determine hidden variables that provide new metrics of cardiac function. Specifically we report on the application of these methods in patients receiving cardiac resynchronisation therapy and ablation for atrial fibrillation.

Published on Sunday 24 April 2016 at 07:00 UTC #event #uq-talk

ECMath Colloquium

ECMath Colloquium

This week's colloquium at the Einstein Center for Mathematics Berlin will be on the topic of “Sparsity: Statistics, Optimization and Applications.” The speakers will be:

  • Peter Richtárik (Edinburgh): Empirical Risk Minimization: Complexity, Duality, Sampling, Sparsity and Big Data
  • Gitta Kutyniok (TU Berlin): Anisotropic Structures and Sparsity-based Regularization
  • Mario Figueiredo (Lisbon): Learning with Strongly Correlated Variables: Ordered Weighted ℓ1 Regularization

Time and Place. Friday 22 April 2016, 14:00–17:00, Humboldt-Universität zu Berlin, Main Building Room 2.094, Unter den Linden 6, 10099 Berlin

Published on Monday 18 April 2016 at 08:00 UTC #event

Introduction to Uncertainty Quantification

Errata for Introduction to Uncertainty Quantification

A list of errata, corrections, and clarifications for Introduction to Uncertainty Quantification can now be found here. In case you spot any mistakes that are not on this list, then please get in touch and I will be happy to post the correction on the errata page.

Published on Monday 11 April 2016 at 11:00 UTC #publication #i2uq

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