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Engineering & Materials Science
# Big Data
# Data Integration
# Machine Learning
# Metadata
# Ontology
# Radiology
# Semantics
# Uncertainty
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Publicaties
Recent
Pathak, S., Schlötterer, J.
, Veltman, J., Geerdink, J.
, Keulen, M. V.
, & Seifert, C. (2024).
Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges.
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
Pathak, S., Schlötterer, J., Geerdink, J., Vijlbrief, O. D.
, Keulen, M. V.
, & Seifert, C. (2023).
Weakly Supervised Learning for Breast Cancer Prediction on Mammograms in Realistic Settings. ArXiv.org.
Wu, B., Xiao, Q., Liu, S., Yin, L., Pechenizkiy, M., Mocanu, D. C.
, Keulen, M. V.
, & Mocanu, E. (2023).
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. ArXiv.org.
https://doi.org/10.48550/arXiv.2312.04727
Maas, J., Römer, J. G. W. T.
, Baysal Erez, I.
, & van Keulen, M. (2023).
Investigating Imputation Methods for Handling Missing Data. Poster session presented at Joint International Scientific Conferences on AI and Machine Learning, BNAIC/BeNeLearn 2023, Delft, Netherlands.
Maas, J., Römer, J. G. W. T.
, Baysal Erez, I.
, & van Keulen, M. (2023).
Investigating Imputation Methods for Handling Missing Data. Paper presented at Joint International Scientific Conferences on AI and Machine Learning, BNAIC/BeNeLearn 2023, Delft, Netherlands.
Xiao, Q.
, Wu, B., Yin, L.
, van Keulen, M., & Pechenizkiy, M. (2023).
Can Less Yield More? Insights into Truly Sparse Training. Poster session presented at ICLR 2023 Workshop on Sparsity in Neural Networks, Kigali, Rwanda.
https://drive.google.com/file/d/1kbWZ9ejU9XvtOMRtAcVYmcoRCDIWj3zy/view
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)
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Vakken Collegejaar 2023/2024
Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.
Vakken Collegejaar 2022/2023
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Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(gebouwnr. 11), kamer 4061
Hallenweg 19
7522NH Enschede
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Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
4061
Postbus 217
7500 AE Enschede