Mathematical aspects of inverse problems summer school

Learn more Add to Calendar 08/29/2017 06:37 PM 09/01/2017 06:37 PM Europe/London Mathematical aspects of inverse problems summer school Location of the event
Tuesday 29 Aug 2017 - Friday 01 Sep 2017
Time: 18:37

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Speakers: Masoumeh Dashti (University of Sussex, UK); Michela Ottobre (Maxwell Institute, Edinburgh); Carola-Bibiane Schoenlieb and Clarice Poon (University of Cambridge,  UK); Alison Fowler (University of Reading, UK) Date: 29 August - 1 September Day 1: 9:00 - 17:45 Day 2: 9:00 - 17:00 Day 3: 9:00 - 17:00 Day 4: 9:00 - 17:00 Venue: The Alan Turing Institute To encourage the participation of female researchers, The Alan Turing Institute is offering scholarships to cover the travel and accommodation expenses for four female participants, to the value of  £600.To apply for this funding, please get in touch with the following information by 7 July: - a short CV (no more than two A4 pages) - a short statement (no more than 150 words) describing your motivation to participate in the summer school



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This summer school will focus on mathematical foundations of inverse problems, at the interface of applied mathematics, statistics and data science. The main aims of the school are to expose the participants to important mathematical concepts and related computational and algorithmic challenges, and to ensure that early career researchers obtain a solid background in some of the mathematical aspects of inverse problems, and the related areas of uncertainty quantification and data assimilation. This workshop is suitable for PhD students and early career researchers with a maths-based degree. Confirmed speakers: Bayesian Approach to Inverse Problems Masoumeh Dashti (University of Sussex, UK) Hamiltonian Monte Carlo Michela Ottobre (Maxwell Institute, Edinburgh) A Comparison of Variational Methods and Deep Neural Networks for Inverse Problems Carola-Bibiane Schoenlieb and Clarice Poon (University of Cambridge,  UK) The Value of Observations for Numerical Weather Prediction Alison Fowler (University of Reading, UK)

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