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Results: 6
Number of items: 6
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Lippe, P., Veeling, B. S., Perdikaris, P., Turner, R. E., & Brandstetter, J. (2023). PDE-Refiner: Achieving Accurate Long Rollouts with Temporal Neural PDE Solvers. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), 37th Conference on Neural Information Processing Systems (NeurIPS 2023): 10-16 December 2023, New Orleans, Louisana, USA (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://doi.org/10.48550/arXiv.2308.05732 -
Löwe, S., O'Connor, P., & Veeling, B. S. (2020). Putting An End to End-to-End: Gradient-Isolated Learning of Representations. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, & R. Garnett (Eds.), 32nd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019 (Vol. 4, pp. 3016-3028). (Advances in Neural Information Processing Systems; Vol. 32). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2019/hash/851300ee84c2b80ed40f51ed26d866fc-Abstract.html
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Hu, S., Worrall, D., Knegt, S., Veeling, B., Huisman, H., & Welling, M. (2019). Supervised Uncertainty Quantification for Segmentation with Multiple Annotations. In D. Shen, T. Liu, T. M. Peters, L. H. Staib, C. Essert, S. Zhou, P.-T. Yap, & A. Khan (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019 : proceedings (Vol. 2, pp. 137-145). (Lecture Notes in Computer Science; Vol. 11765). Springer. https://doi.org/10.1007/978-3-030-32245-8_16
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Veeling, B., Linmans, J., Winkens, J., Cohen, T., & Welling, M. (2018, June 8). PatchCamelyon (PCam) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.1494286
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Veeling, B. S., van den Berg, R., & Welling, M. (2018). Predictive Uncertainty through Quantization. (1 ed.) University of Amsterdam. https://arxiv.org/abs/1810.05500v1
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