Papers accepted at AISTATS 2021

We got two papers accepted at this year’s AISTATS conference: “False Discovery Rates in Biological Networks” with Lu Yu and Tobias Kaufmann and “Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery” with Mike Laszkiewicz and Asja Fischer. Congratulations especially to the PhD students Lu (Toronto) and Mike (Bochum)! 🥳

Grant Awarded

Our grant proposal A general framework for graphical models was selected for funding by the German Research Foundation. We are looking forward to working on an exciting topic! 🎬

Inference in Labor Economics

We have now put our paper “A pipeline for variable selection and false discovery rate control with an application in labor economics” on arXiv. The paper will be part of the Annual Congress of the Swiss Society of Economics and Statistics in 2021. Congratulations Sophie-Charlotte!