M. Nauta MSc (Meike)

Nauta, M., Hegeman, J. H., Geerdink, J., Schlötterer, J. , Keulen, M. V. , & Seifert, C. (2024). Interpreting and Correcting Medical Image Classification with PIP-Net. In S. Nowaczyk, P. Biecek, N. C. Chung, M. Vallati, P. Skruch, J. Jaworek-Korjakowska, S. Parkinson, A. Nikitas, M. Atzmüller, T. Kliegr, U. Schmid, S. Bobek, N. Lavrac, M. Peeters, R. van Dierendonck, S. Robben, E. Mercier-Laurent, G. Kayakutlu, M. L. Owoc, K. Mason, A. Wahid, P. Bruno, F. Calimeri, F. Cauteruccio, G. Terracina, D. Wolter, J. L. Leidner, M. Kohlhase, ... V. Dimitrova (Eds.), Artificial Intelligence. ECAI 2023 International Workshops - XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, 2023, Proceedings (pp. 198-215). (Communications in Computer and Information Science; Vol. 1947). Springer. https://doi.org/10.1007/978-3-031-50396-2_11

Nauta, M., Hegeman, J. H., Geerdink, J., Schlötterer, J. , Keulen, M. V. , & Seifert, C. (2023). Interpreting and Correcting Medical Image Classification with PIP-Net. ArXiv.org. https://doi.org/10.48550/arXiv.2307.10404

Nauta, M. , & Seifert, C. (2023). The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers. In L. Longo (Ed.), Explainable Artificial Intelligence: 1st World Conference, xAI 2023, 2023, Proceedings (pp. 397-420). (Communications in Computer and Information Science; Vol. 1901 CCIS). Springer. https://doi.org/10.1007/978-3-031-44064-9_21

Nguyen, E. , Nauta, M. , Englebienne, G. , & Seifert, C. (2023). Feature Attribution Explanations for Spiking Neural Networks. In Proceedings - 2023 IEEE 5th International Conference on Cognitive Machine Intelligence, CogMI 2023 (pp. 59-68). IEEE. https://doi.org/10.1109/CogMI58952.2023.00018

Le, P. Q. , Nauta, M. , Nguyen, V. B. , Pathak, S., Schlötterer, J. , & Seifert, C. (2023). Benchmarking eXplainable AI: A Survey on Available Toolkits and Open Challenges. In E. Elkind (Ed.), Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 (pp. 6665-6673). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2023-August). International Joint Conferences on Artificial Intelligence.

Kelly, U. M. , Nauta, M., Liu, L. , Spreeuwers, L. J. , & Veldhuis, R. N. J. (2023). Worst-Case Morphs using Wasserstein ALI and Improved MIPGAN. https://doi.org/10.48550/arXiv.2310.08371

Nauta, M., Schlötterer, J. , van Keulen, M. , & Seifert, C. (2023). PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification. Abstract from 2nd Explainable AI for Computer Vision Workshop, XAI4CV 2023, Vancouver, British Columbia, Canada.

Nauta, M., Schlötterer, J. , van Keulen, M. , & Seifert, C. (2023). PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification. In CVPR 2023 (pp. 2744-2753)

Borys, K., Schmitt, Y. A. , Nauta, M. , Seifert, C., Krämer, N., Friedrich, C. M., & Nensa, F. (2023). Explainable AI in medical imaging: An overview for clinical practitioners - Saliency-based XAI approaches. European journal of radiology, 162, 110787. https://doi.org/10.1016/j.ejrad.2023.110787

Nauta, M. (2023). Explainable AI and Interpretable Computer Vision: From Oversight to Insight. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036555753