# Research

My research interests lie at the intersection of machine learning and applied mathematics. In particular this includes the following topics:

- Representational capacity of neural networks
- Connections between neural networks and differential equations
- Geometry of optimal control problems, in particular structural properties of optimal policies

**Poster presentations**

Johannes Müller, Marius Zeinhofer (2020)

**Deep Ritz revisited**

*ICLR workshop on Integration of Deep Neural Models and Differential Equations*

fulltext available | ICLR workshop DeepDiffEqJohannes Müller (2020)

**On the space-time expressivity of residual networks**

*ICLR workshop on Integration of Deep Neural Models and Differential Equations*

fulltext available | ICLR workshop DeepDiffEq

**Thesis**

During my MSc studies at the University of Warwick I was supervised by Nikos Zygouras and Theo Damoulas and completed my thesis on the parameter estimation of determinantal point processes. You can find the PDF here.

At the University of Freiburg, I studied the approximation capabilities of deep residual networks under the supervision of Philipp Harms and the thesis is available here.