Casual Causality

I am a Ph.D. student at the University of Tübingen, supervised by Wieland Brendel, Ferenc Huszár, Matthias Bethge, and Bernhard Schölkopf. I am part of the ELLIS and IMPRS-IS programs. My main research interests include causal representation learning and identifiability. I have done both my M.Sc. and B.Sc. at the Budapest University of Technology in electrical engineering and specialized in control engineering and intelligent systems. In my free time, I enjoy being outdoors and often bring my camera with me.

AMMI 3 Notes: Geometric priors I

15 minute read


In the previous post, we dived deep into abstract algebra to motivate why Geometric Deep Learning is an interesting topic. Now we begin the journey to show that it is also useful in practice. In summary, we know that symmetries constrain our hypothesis class, making learning simpler—indeed, they can make learning a tractable problem. How does this happen?

LaTeX tricks

8 minute read


Improve typesetting and save space in your submissions, who does not want that?

Welcome to my journey!

less than 1 minute read


A PhD student’s casual journey with causal inference.