Investigating the Importance of Demographic Features for EDM-Predictions. - Lea Cohausz; Andrej Tschalzev; Christian Bartelt; Heiner Stuckenschmidt (EDM, 2023)

Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods. - Andrej Tschalzev; Paul Nitschke; Lukas Kirchdorfer; Stefan Lüdtke; Christian Bartelt; Heiner Stuckenschmidt (IJCAI, 2024)

A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data. - Andrej Tschalzev; Sascha Marton; Stefan Lüdtke; Christian Bartelt; Heiner Stuckenschmidt (NeurIPS, 2024)

Explaining neural networks without access to training data. - Sascha Marton; Stefan Lüdtke; Christian Bartelt; Andrej Tschalzev; Heiner Stuckenschmidt (Mach. Learn., 2024)

Unreflected Use of Tabular Data Repositories Can Undermine Research Quality. - Andrej Tschalzev; Lennart Purucker; Stefan Lüdtke; Frank Hutter; Christian Bartelt; Heiner Stuckenschmidt (CoRR, 2025)

TabArena: A Living Benchmark for Machine Learning on Tabular Data. - Nick Erickson; Lennart Purucker; Andrej Tschalzev; David Holzmüller; Prateek Mutalik Desai; David Salinas; Frank Hutter (CoRR, 2025)