Rethinking Assumptions in Deep Anomaly Detection. - Lukas Ruff; Robert A. Vandermeulen; Billy Joe Franks; Klaus-Robert Müller; Marius Kloft (CoRR, 2020)

Explainable Deep One-Class Classification. - Philipp Liznerski; Lukas Ruff; Robert A. Vandermeulen; Billy Joe Franks; Marius Kloft; Klaus-Robert Müller (ICLR, 2021)

Trainability for Universal GNNs Through Surgical Randomness. - Billy Joe Franks; Markus Anders; Marius Kloft; Pascal Schweitzer (CoRR, 2021)

Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images. - Philipp Liznerski; Lukas Ruff; Robert A. Vandermeulen; Billy Joe Franks; Klaus-Robert Müller; Marius Kloft (Trans. Mach. Learn. Res., 2022)

Ordinal Regression for Difficulty Prediction of StepMania Levels. - Billy Joe Franks; Benjamin Dinkelmann; Marius Kloft; Sophie Fellenz (ECML/PKDD (6), 2023)

Ordinal Regression for Difficulty Estimation of StepMania Levels. - Billy Joe Franks; Benjamin Dinkelmann; Sophie Fellenz; Marius Kloft (CoRR, 2023)

Deep Anomaly Detection on Tennessee Eastman Process Data. - Fabian Hartung; Billy Joe Franks; Tobias Michels; Dennis Wagner; Philipp Liznerski; Steffen Reithermann; Sophie Fellenz; Fabian Jirasek; Maja Rudolph; Daniel Neider; Heike Leitte; Chen Song; et al. (CoRR, 2023)

A Systematic Approach to Universal Random Features in Graph Neural Networks. - Billy Joe Franks; Markus Anders; Marius Kloft; Pascal Schweitzer (Trans. Mach. Learn. Res., 2023)

Weisfeiler-Leman at the margin: When more expressivity matters. - Billy Joe Franks; Christopher Morris 001; Ameya Velingker; Floris Geerts (ICML, 2024)

Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. - Billy Joe Franks; Moshe Eliasof; Semih Cantürk; Guy Wolf; Carola-Bibiane Schönlieb; Sophie Fellenz; Marius Kloft (Trans. Mach. Learn. Res., 2025)