Our new paper “Benchmarking the fairness of image upsampling methods” is now on arXiv. Awesome job, Mike—and thanks Imant, Julia, and Asja for the great collaboration! 🇩🇪🇨🇭🏴☠️
Change points in time series
Our discussion paper in JRSSB about “Probabilistic and Statistical Aspects of Machine Learning” is available online. Congratulations, Ayla! 🇬🇧
Affine Invariance in Neural Networks
Our new paper “Affine invariance in continuous-domain convolutional neural networks” is now on arXiv. Well done, Ali! 🖥
New PhD Student on Board
Benedikt Lüdtke Schwienhorst joins us as a PhD student here in Hamburg. He is co-advised by Nadja Klein (TU Dortmund). Welcome, Benedikt! 🚁
Teaching
This semester, we are offering a course on high-dimensional statistics and a seminar on statistical learning. The course might be of interest to students in mathematics and well beyond (CS, physics, biology …)—feel free to check out the details on STiNE.
University of Hamburg
Our team has moved to University of Hamburg. Thank you for the warm welcome here in Hamburg. We are excited to start contributing to the UHH community! 🚢 🌊 🎇
Watermarking
Our new paper “Set-membership inference attacks using data watermarking” is now on arXiv. Nicely done, Mike, Denis, and Asja! 🚀🚀🚀
Deep generative models
We have put a new paper called “Single-model attribution via final-layer inversion” about deep generative models on arXiv. Wonderful job, Mike, Jonas, and Asja! 🥁🎷🪗🎻
High-Dimensional Extremes
Together with our amazing collaborator Marco Oesting, we have put a new paper with the title “Extremes in high dimensions: methods and scalable algorithms” on arXiv. Thanks for the great work, Marco! 🍻
Lag selection and stability in AR processes
With Somnath and our collaborator Rainer von Sachs, we have put a new paper with the title “Lag selection and estimation of stable parameters for multiple autoregressive processes through convex programming” on arXiv. Well done, Somnath! 🥇
Johannes Lederer 