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.

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.

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.

M. Loog, T.J. Viering, A. Mey (2019), Minimizers of the empirical risk and risk monotonicity, In Neural Information Processing Systems.

Y. Zeng, J. C.A. van der Lubbe, M. Loog (2019), Multi-scale convolutional neural network for pixel-wise reconstruction of Van Gogh’s drawings, In Machine Vision and Applications Volume 30 p.1229-1241.

Tom J. Viering, Jesse H. Krijthe, Marco Loog (2019), Nuclear discrepancy for single-shot batch active learning, In Machine Learning Volume 108 p.1561-1599.