Rotation equivariant CNNs for digital pathology BS Veeling, J Linmans, J Winkens, T Cohen, M Welling Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 646 | 2018 |
How good is the Bayes posterior in deep neural networks really? F Wenzel, K Roth, BS Veeling, J Świątkowski, L Tran, S Mandt, J Snoek, ... arXiv preprint arXiv:2002.02405, 2020 | 401 | 2020 |
Putting an end to end-to-end: Gradient-isolated learning of representations S Löwe, P O'Connor, B Veeling Advances in neural information processing systems 32, 2019 | 150 | 2019 |
Supervised uncertainty quantification for segmentation with multiple annotations S Hu, D Worrall, S Knegt, B Veeling, H Huisman, M Welling Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 109 | 2019 |
Towards radiologist-level cancer risk assessment in CT lung screening using deep learning S Trajanovski, D Mavroeidis, CL Swisher, BG Gebre, BS Veeling, ... Computerized Medical Imaging and Graphics 90, 101883, 2021 | 71 | 2021 |
Learning sub-sampling and signal recovery with applications in ultrasound imaging IAM Huijben, BS Veeling, K Janse, M Mischi, RJG van Sloun IEEE Transactions on Medical Imaging 39 (12), 3955-3966, 2020 | 66 | 2020 |
The k-tied normal distribution: A compact parameterization of Gaussian mean field posteriors in Bayesian neural networks J Swiatkowski, K Roth, B Veeling, L Tran, J Dillon, J Snoek, S Mandt, ... International conference on machine learning, 9289-9299, 2020 | 64 | 2020 |
Hydra: Preserving ensemble diversity for model distillation L Tran, BS Veeling, K Roth, J Swiatkowski, JV Dillon, J Snoek, S Mandt, ... arXiv preprint arXiv:2001.04694, 2020 | 55 | 2020 |
Pde-refiner: Achieving accurate long rollouts with neural pde solvers P Lippe, B Veeling, P Perdikaris, R Turner, J Brandstetter Advances in Neural Information Processing Systems 36, 67398-67433, 2023 | 54 | 2023 |
Fast protein backbone generation with SE (3) flow matching J Yim, A Campbell, AYK Foong, M Gastegger, J Jiménez-Luna, S Lewis, ... arXiv preprint arXiv:2310.05297, 2023 | 51 | 2023 |
Deep probabilistic subsampling for task-adaptive compressed sensing I Huijben, BS Veeling, RJG van Sloun 8th International Conference on Learning Representations, ICLR 2020, 2020 | 46 | 2020 |
Learning sampling and model-based signal recovery for compressed sensing MRI IAM Huijben, BS Veeling, RJG van Sloun ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 40 | 2020 |
Probabilistic multileave for online retrieval evaluation A Schuth, RJ Bruintjes, F Buüttner, J van Doorn, C Groenland, ... Proceedings of the 38th international ACM SIGIR Conference on Research and …, 2015 | 39 | 2015 |
Sample efficient semantic segmentation using rotation equivariant convolutional networks J Linmans, J Winkens, BS Veeling, TS Cohen, M Welling arXiv preprint arXiv:1807.00583, 2018 | 26 | 2018 |
Active deep probabilistic subsampling H Van Gorp, I Huijben, BS Veeling, N Pezzotti, RJG Van Sloun International Conference on Machine Learning, 10509-10518, 2021 | 23 | 2021 |
Improved semantic segmentation for histopathology using rotation equivariant convolutional networks J Winkens, J Linmans, BS Veeling, TS Cohen, M Welling | 20 | 2018 |
Improved motif-scaffolding with SE (3) flow matching J Yim, A Campbell, E Mathieu, AYK Foong, M Gastegger, J Jiménez-Luna, ... ArXiv, 2024 | 19 | 2024 |
Dynamic probabilistic pruning: A general framework for hardware-constrained pruning at different granularities L Gonzalez-Carabarin, IAM Huijben, B Veeling, A Schmid, RJG van Sloun IEEE Transactions on Neural Networks and Learning Systems 35 (1), 733-744, 2022 | 12 | 2022 |
Improving visitor traffic forecasting in brick-and-mortar retail stores with neural networks B Veeling Bachelor thesis, Universiteit Twente, 2014 | 6 | 2014 |
Greedy infomax for self-supervised representation learning S Löwe, P O’Connor, BS Veeling Master Thesis, MSc Artificial Intelligence, University of Amsterdam. Source, 2019 | 4 | 2019 |