Onur Teymur

I am Lecturer in Statistics at the University of Kent, and visiting researcher at the Alan Turing Institute in London.

I am interested in Bayesian statistical theory and, increasingly, in nonparametric Bayesian approaches.

I also work in Bayesian computation, and in particular am involved with the emerging field of probabilistic numerical methods.

How are ya, champ?

Not so bad, thanks for asking.

Three-line CV

I was previously a postdoc at Newcastle University (2020-21), and before that at Imperial College London (2018-20), where I was also a postgraduate (2013-18).

Some publications

1. Teymur, Foley, Breen, Karvonen & Oates (2021)  Black Box Probabilistic Numerics;   arXiv:2106.13718

2. Cockayne, Graham, Oates, Sullivan & Teymur (2021)  Testing whether a learning procedure is calibrated;   arXiv:2012.12670

3. South, Riabiz, Teymur & Oates (2021)  Post-Processing of MCMC;   arXiv:2103.16048   (forthcoming in Annual Review of Statistics and Its Application)

4. Teymur, Gorham, Riabiz & Oates (2020)  Optimal quantisation of probability measures using Maximum Mean Discrepancy;   AISTATS 2021 & arXiv:2010.07064

5. Teymur & Filippi (2020)  A Bayesian nonparametric test for conditional independence;  Foundations of Data Science & arXiv:1910.11219

6. Teymur, Lie, Sullivan & Calderhead (2018)  Implicit probabilistic integrators for ODEs;  NeurIPS 2018 & arXiv:1805.07970

7. Teymur, Zygalakis & Calderhead (2016)  Probabilistic linear multistep methods;  NeurIPS 2016 & arXiv:1610.08417

September 2021