Presentation
Post-doc researcher at Max Planck Institute for Mathematics in the Sciences, where I am fortunate to work with Professor Dr. Sayan Mukherjee. Before that I was a post-doc researcher at Max Planck Institute for Mathematics in the Sciences, where I was fortunate to have worked with Professor Dr. Guido Montúfar. Before that, I did my PhD in Mathematical Statistics in the Department of Mathematics at Humboldt University of Berlin, where I worked under the supervision of Professor Dr. Markus Reiss. My research interests lie at the intersection of nonparametric statistics and machine learning. Recently, I have become interested in minimax optimization problems and mathematics of deep learning with applications in biostatistics and finance.
CV: [PDF]
Email: katerina.papagiannouli [at) mis.mpg.de
Research
Publications
Papagiannouli, K. Minimax rates for the covariance estimation of multi-dimensional Lévy processes with high-frequency data, Electronic Journal of Statistics, 2020. [PDF]
Papagiannouli, K. A Lepski-type stopping rule for the covariance estimation of multi-dimensional Lévy processes, Statistical Inference for Stochastic Processes, Springer, 2021. [PDF]
3. Brechét P., Papagiannouli, K., An J.,Montufar G. Convergence of Generative Deep Linear Networks trained with Bures-Wasserstein Loss, ICML 2023 [PDF]