1. 2019
  2. Learning an MR acquisition-invariant representation using Siamese neural networks

    Kouw, W., Loog, M., Bartels, W. & Mendrik, A., 2019, (Accepted/In press) Proceedings of the IEEE International Symposium on Biomedical Imaging. IEEE

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  3. PRECISE: A domain adaptation approach to transfer predictors of drug response from pre-clinical models to tumors

    Mourragui, S., Loog, M., van der Wiel, M. A., Reinders, M. & Wessels, L., 2019, In : Bioinformatics. 35, 14, p. i510-i519 10 p., btz372.

    Research output: Contribution to journalArticleScientificpeer-review

  4. Single shot active learning using pseudo annotators

    Yang, Y. & Loog, M., 2019, In : Pattern Recognition. 89, p. 22-31 10 p.

    Research output: Contribution to journalArticleScientificpeer-review

  5. The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning

    Krijthe, J. & Loog, M., 2019, (Accepted/In press) Advances in Neural Information Processing Systems. p. 1793-1802 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientific

  6. 2018
  7. A benchmark and comparison of active learning for logistic regression

    Yang, Y. & Loog, M., 2018, In : Pattern Recognition. 83, p. 401-415 15 p.

    Research output: Contribution to journalArticleScientificpeer-review

  8. A variance maximization criterion for active learning

    Yang, Y. & Loog, M., 2018, In : Pattern Recognition. 78, p. 358-370 13 p.

    Research output: Contribution to journalArticleScientificpeer-review

  9. Contextual loss functions for optimization of convolutional neural networks generating pseudo CTs from MRI

    van Stralen, M., Zhou, Y., Wozny, P. J., Seevinck, P. R. & Loog, M., 2018, Medical Imaging 2018: Image Processing. Angelini, E. D. & Landman, B. A. (eds.). Bellingham: SPIE, p. 105741N-1 - 105741N-6 6 p. 105741N. (Proceedings of Spie; vol. 10574).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  10. Effects of sampling skewness of the importance-weighted risk estimator on model selection

    Kouw, W. & Loog, M., 2018, 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, p. 1468-1473 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  11. Gradient descent for gaussian processes variance reduction

    Bottarelli, L. & Loog, M., 2018, Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. Bai, X., Hancock, E. R., Ho, T. K., Wilson, R. C., Biggio, B. & Robles-Kelly, A. (eds.). Cham: Springer Verlag, p. 160-169 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11004 ).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  12. Protein remote homology detection using dissimilarity-based multiple instance learning

    Mensi, A., Bicego, M., Lovato, P., Loog, M. & Tax, D. M. J., 2018, Structural, Syntactic, and Statistical Pattern Recognition : Joint IAPR International Workshop, S+SSPR 2018, Proceedings. Bai, X., Hancock, E. R., Ho, T. K., Wilson, R. C., Biggio, B. & Robles-Kelly, A. (eds.). Cham: Springer Verlag, p. 119-129 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11004 ).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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