Alexander Mey, Tom Julian Viering, Marco Loog (2020), A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization, Michael R. Berthold, Ad Feelders, Georg Krempl (Eds.), In Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Proceedings Volume 12080 p.326-338, SpringerOpen.

Marco Loog, Tom Viering, Alexander Mey, Jesse H. Krijthe, David M. J. Tax (2020), A brief prehistory of double descent, In Proceedings of the National Academy of Sciences of the United States of America p.10625-10626.

Kasra Arnavaz, Aasa Feragen, Oswin Krause, Marco Loog (2020), Bayesian active learning for maximal information gain on model parameters, In Proceedings of ICPR 2020 - 25th International Conference on Pattern Recognition p.10524-10531, IEEE.

Katja Geertruida Schmahl, Tom Julian Viering, Stavros Makrodimitris, Arman Naseri Jahfari, David Tax, Marco Loog (2020), Is Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings, In Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science p.94-103, Association for Computational Linguistics.

Tom Julian Viering, Alexander Mey, Marco Loog (2020), Making Learners (More) Monotone, Michael R. Berthold, Ad Feelders, Georg Krempl (Eds.), In Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Proceedings Volume 12080 p.535-547, SpringerOpen.

Julius von Kügelgen, Alexander Mey, Marco Loog (2020), Semi-generative modelling: Covariate-shift adaptation with cause and effect features, In Proceedings of Machine Learning Research.

Julius von Kügelgen, Alexander Mey, Marco Loog, Bernhard Schölkopf (2020), Semi-supervised learning, causality, and the conditional cluster assumption, Jonas Peters, David Sontag (Eds.), In Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence, UAI 2020 Volume 124 p.1-10.

Antonella Mensi, Manuele Bicego, Pietro Lovato, Marco Loog, David M.J. Tax (2019), A dissimilarity-based multiple instance learning approach for protein remote homology detection, In Pattern Recognition Letters Volume 128 p.231-236.

Lorenzo Bottarelli, Marco Loog (2019), Gaussian process variance reduction by location selection, In Pattern Recognition Letters Volume 125 p.727-734.

W.M. Kouw, M. Loog, L.W. Bartels, A.M. Mendrik (2019), Learning an MR acquisition-invariant representation using Siamese neural networks, In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019) p.364-367, IEEE.