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Results: 8
Number of items: 8
  • Open Access
    Van Der Pol, E., Worrall, D., Van Hoof, H., Oliehoek, F., & Welling, M. (2021). MDP homomorphic networks: Group symmetries in reinforcement learning. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), 34th Concerence on Neural Information Processing Systems (NeurIPS 2020): online, 6-12 December 2020 (Vol. 6, pp. 4199-4210). (Advances in Neural Information Processing Systems; Vol. 33). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2020/hash/2be5f9c2e3620eb73c2972d7552b6cb5-Abstract.html
  • Open Access
    Fuchs, F., Worrall, D., Fischer, V., & Welling, M. (2021). SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), 34th Concerence on Neural Information Processing Systems (NeurIPS 2020): online, 6-12 December 2020 (Vol. 3, pp. 1970-1981). (Advances in Neural Information Processing Systems; Vol. 33). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2020/hash/15231a7ce4ba789d13b722cc5c955834-Abstract.html
  • Open Access
    Worrall, D., & Welling, M. (2020). Deep Scale-spaces: Equivariance Over Scale. 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. 10, pp. 7334-7346). (Advances in Neural Information Processing Systems; Vol. 32). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2019/hash/f04cd7399b2b0128970efb6d20b5c551-Abstract.html
  • van der Ouderaa, T. F. A., & Worrall, D. E. (2019). Reversible GANs for memory-efficient image-to-image translation. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : 16-20 June 2019, Long Beach, California (pp. 4715-4723). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR.2019.00485
  • Open Access
    Diaconu, N., & Worrall, D. (2019). Learning to convolve: A generalized weight-tying approach. Proceedings of Machine Learning Research, 97, 1586-1595. http://proceedings.mlr.press/v97/diaconu19a.html
  • 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
  • Open Access
    van der Ouderaa, T. F. A., Worrall, D. E., & van Ginneken, B. (2019). Chest CT Super-resolution and Domain-adaptation using Memory-efficient 3D Reversible GANs. Paper presented at 2nd International Conference on Medical Imaging with Deep Learning, London, United Kingdom. https://doi.org/10.48550/arXiv.1908.00295
  • Open Access
    Diaconu, N., & Worrall, D. (2019). Affine Self Convolution. (v1 ed.) ArXiv. https://arxiv.org/abs/1911.07704
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