Maximum Class Separation as Inductive Bias in One Matrix. - Tejaswi Kasarla; Gertjan J. Burghouts; Max van Spengler; Elise van der Pol; Rita Cucchiara; Pascal Mettes (NeurIPS, 2022)

Poincaré ResNet. - Max van Spengler; Erwin Berkhout; Pascal Mettes (ICCV, 2023)

HypLL: The Hyperbolic Learning Library. - Max van Spengler; Philipp Wirth; Pascal Mettes (ACM Multimedia, 2023)

Adversarial Attacks on Hyperbolic Networks. - Max van Spengler; Jan Zahálka; Pascal Mettes (ECCV Workshops (17), 2024)

Designing Hierarchies for Optimal Hyperbolic Embedding. - Melika Ayoughi; Max van Spengler; Pascal Mettes; Paul Groth (ESWC (1), 2025)

Compositional Entailment Learning for Hyperbolic Vision-Language Models. - Avik Pal; Max van Spengler; Guido Maria D'Amely di Melendugno; Alessandro Flaborea; Fabio Galasso; Pascal Mettes (ICLR, 2025)

Low-distortion and GPU-compatible Tree Embeddings in Hyperbolic Space. - Max van Spengler; Pascal Mettes (CoRR, 2025)

Balanced Hyperbolic Embeddings Are Natural Out-of-Distribution Detectors. - Tejaswi Kasarla; Max van Spengler; Pascal Mettes (CoRR, 2025)