Avoiding Discrimination through Causal Reasoning. - Niki Kilbertus; Mateo Rojas-Carulla; Giambattista Parascandolo; Moritz Hardt; Dominik Janzing; Bernhard Schölkopf (NIPS, 2017)

Discriminative k-shot learning using probabilistic models. - Matthias Bauer 001; Mateo Rojas-Carulla; Jakub Bartlomiej Swiatkowski; Bernhard Schölkopf; Richard E. Turner (CoRR, 2017)

Causal Discovery Using Proxy Variables. - Mateo Rojas-Carulla; Marco Baroni; David Lopez-Paz (ICLR (Workshop), 2018)

Learning Independent Causal Mechanisms. - Giambattista Parascandolo; Niki Kilbertus; Mateo Rojas-Carulla; Bernhard Schölkopf (ICML, 2018)

Invariant Models for Causal Transfer Learning. - Mateo Rojas-Carulla; Bernhard Schölkopf; Richard E. Turner; Jonas Peters (J. Mach. Learn. Res., 2018)

GeNet: Deep Representations for Metagenomics. - Mateo Rojas-Carulla; Ilya O. Tolstikhin; Guillermo Luque; Nicholas D. Youngblut; Ruth E. Ley; Bernhard Schölkopf (CoRR, 2019)

Learning transferable representations - Mateo Rojas-Carulla (2019)

DeepMAsED: evaluating the quality of metagenomic assemblies. - Olga Mineeva; Mateo Rojas-Carulla; Ruth E. Ley; Bernhard Schölkopf; Nicholas D. Youngblut (Bioinform., 2020)

Recommendations on test datasets for evaluating AI solutions in pathology. - André Homeyer; Christian Geißler; Lars Ole Schwen; Falk Zakrzewski; Theodore Evans; Klaus Strohmenger; Max Westphal; Roman David Bülow; Michaela Kargl; Aray Karjauv; Isidre Munné-Bertran; Carl Orge Retzlaff; et al. (CoRR, 2022)

Gandalf the Red: Adaptive Security for LLMs. - Niklas Pfister; Václav Volhejn; Manuel Knott 003; Santiago Arias; Julia Bazinska; Mykhailo Bichurin; Alan Commike; Janet Darling; Peter Dienes; Matthew Fiedler; David Haber; Matthias Kraft; et al. (CoRR, 2025)