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Results: 363
Number of items: 363
  • Open Access
    Strezoski, G. (2022). Information sharing methods for multi-task learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Bartels, M. G. C., Najdenkoska, I., van de Leur, R. R., Sammani, A., Taha, K., Knigge, D. M., Doevendans, P. A., Worring, M., & van Es, R. (2022). Learning to Automatically Generate Accurate ECG Captions. Proceedings of Machine Learning Research, 172, 86-102. https://proceedings.mlr.press/v172/bartels22a.html
  • Open Access
    Macarulla Rodriguez, A., Geradts, Z., & Worring, M. (2022). Calibration of score based likelihood ratio estimation in automated forensic facial image comparison. Forensic Science International, 334, Article 111239. https://doi.org/10.1016/j.forsciint.2022.111239
  • Open Access
    Najdenkoska, I., Zhen, X., Worring, M., & Shao, L. (2022). Uncertainty-aware report generation for chest X-rays by variational topic inference. Medical Image Analysis, 82, Article 102603. https://doi.org/10.1016/j.media.2022.102603
  • Open Access
    Arya, D. (2022). Multimodal deep learning on hypergraphs. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    van Noord, N., Wevers, M., Blanke, T., Noordegraaf, J., & Worring, M. (2022). An Analytics of Culture: Modeling Subjectivity, Scalability, Contextuality, and Temporality. Paper presented at Cultures in AI/AI in Culture. https://doi.org/10.48550/arXiv.2211.07460
  • Open Access
    Derakhshani, M. M., Najdenkoska, I., van Sonsbeek, T., Zhen, X., Mahapatra, D., Worring, M., & Snoek, C. G. M. (2022). LifeLonger: A Benchmark for Continual Disease Classification. In L. Wang, Q. Dou, P. T. Fletcher, S. Speidel, & S. Li (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference, Singapore, September 18–22, 2022 : proceedings (Vol. II, pp. 314–324). (Lecture Notes in Computer Science; Vol. 13432). Springer. https://doi.org/10.48550/arXiv.2204.05737, https://doi.org/10.1007/978-3-031-16434-7_31
  • Open Access
    Shao, L., Shen, J., Worring, M., & Zhen, X. (2022). Variational Multi-Task Learning with Gumbel-Softmax Priors. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. Wortman Vaughan (Eds.), 35th Conference on Neural Information Processing Systems (NeurIPS 2021) : online, 6-14 December 2021 (Vol. 25, pp. 21031-21042). (Advances in Neural Information Processing Systems; Vol. 34). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2021/hash/afd4836712c5e77550897e25711e1d96-Abstract.html
  • Najdenkoska, I., Zhen, X., Worring, M., & Shao, L. (2021). Variational Topic Inference for Chest X-Ray Report Generation. In M. de Bruijne, P. C. Cattin, S. Cotin, N. Padoy, S. Speidel, Y. Zheng, & C. Essert (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021 : proceedings (Vol. III, pp. 625-635). (Lecture Notes in Computer Science; Vol. 12903). Springer. https://doi.org/10.1007/978-3-030-87199-4_59
  • van Sonsbeek, T., Zhen, X., Worring, M., & Shao, L. (2021). Variational Knowledge Distillation for Disease Classification in Chest X-Rays. In A. Feragen, S. Sommer, J. Schnabel, & M. Nielsen (Eds.), Information Processing in Medical Imaging: 27th International Conference, IPMI 2021, virtual event, June 28–June 30, 2021 : proceedings (pp. 334-345). (Lecture Notes in Computer Science; Vol. 12729). Springer. https://doi.org/10.1007/978-3-030-78191-0_26
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