Office 20-30/A21

Maria-von-Linden-Str. 6

D-72076 Tübingen

# Marvin Pförtner

I am a PhD student in Philipp Hennig’s group at the University of Tübingen and the International Max Planck Research School for Intelligent Systems (IMPRS-IS). My research interests lie at the intersection of Bayesian machine learning and numerical analysis. More specifically, my work revolves around

- algorithms for scalable (approximate) Gaussian process inference,
- Gaussian process theory (sample path properties, Gaussian measure theory),
- probabilistic numerical methods for partial differential equations, and
- Bayesian deep learning with Laplace approximations.

I’m also interested in applications of all the above to scientific inference tasks.

I like to tackle problems using the framework of matrix-free (probabilistic) numerical linear algebra, which often leads to elegant and efficient algorithms.

## news

Nov 28, 2023 | I will give a tutorial at the Probabilistic Numerics Spring School 2024 taking place in Southampton on the 8th and 9th of April. |
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Jun 29, 2023 | I will give a talk at the CRiSM Workshop on “Fusing Simulation with Data Science” at the University of Warwick on July 18. |

May 1, 2023 | I will give talks at the University of Cambridge (May 3), at the University of Southampton (May 4), and at UCL (May 5). |