| Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge S Bakas, B Menze, M Reyes, et al. arXiv preprint arXiv:1811.02629, 2018 | 379 | 2018 |
| Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation K Kamnitsas, W Bai, E Ferrante, S McDonagh, M Sinclair, N Pawlowski, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018 | 238 | 2018 |
| Rasa: Open source language understanding and dialogue management T Bocklisch, J Faulkner, N Pawlowski, A Nichol arXiv preprint arXiv:1712.05181, 2017 | 136 | 2017 |
| Implicit weight uncertainty in neural networks N Pawlowski, A Brock, MCH Lee, M Rajchl, B Glocker arXiv preprint arXiv:1711.01297, 2017 | 53 | 2017 |
| Dltk: State of the art reference implementations for deep learning on medical images N Pawlowski, SI Ktena, MCH Lee, B Kainz, D Rueckert, B Glocker, ... arXiv preprint arXiv:1711.06853, 2017 | 48 | 2017 |
| Automating morphological profiling with generic deep convolutional networks N Pawlowski, JC Caicedo, S Singh, AE Carpenter, A Storkey BioRxiv, 085118, 2016 | 35* | 2016 |
| Feature control as intrinsic motivation for hierarchical reinforcement learning N Dilokthanakul, C Kaplanis, N Pawlowski, M Shanahan IEEE transactions on neural networks and learning systems 30 (11), 3409-3418, 2019 | 34 | 2019 |
| Multi-modal learning from unpaired images: Application to multi-organ segmentation in ct and mri VV Valindria, N Pawlowski, M Rajchl, I Lavdas, EO Aboagye, AG Rockall, ... 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 547-556, 2018 | 33 | 2018 |
| Unsupervised lesion detection in brain CT using bayesian convolutional autoencoders N Pawlowski, MCH Lee, M Rajchl, S McDonagh, E Ferrante, K Kamnitsas, ... | 29 | 2018 |
| Deep generative models in the real-world: An open challenge from medical imaging X Chen, N Pawlowski, M Rajchl, B Glocker, E Konukoglu arXiv preprint arXiv:1806.05452, 2018 | 28 | 2018 |
| CytoGAN: Generative modeling of cell images P Goldsborough, N Pawlowski, JC Caicedo, S Singh, AE Carpenter bioRxiv, 227645, 2017 | 27* | 2017 |
| TETRIS: template transformer networks for image segmentation with shape priors MCH Lee, K Petersen, N Pawlowski, B Glocker, M Schaap IEEE transactions on medical imaging 38 (11), 2596-2606, 2019 | 21 | 2019 |
| Neuronet: fast and robust reproduction of multiple brain image segmentation pipelines M Rajchl, N Pawlowski, D Rueckert, PM Matthews, B Glocker arXiv preprint arXiv:1806.04224, 2018 | 19 | 2018 |
| A portable diagnostic device for cardiac magnetic field mapping JW Mooney, S Ghasemi-Roudsari, ER Banham, C Symonds, ... Biomedical Physics & Engineering Express 3 (1), 015008, 2017 | 15 | 2017 |
| Needles in haystacks: On classifying tiny objects in large images N Pawlowski, S Bhooshan, N Ballas, F Ciompi, B Glocker, M Drozdzal arXiv preprint arXiv:1908.06037, 2019 | 7 | 2019 |
| Efficient variational Bayesian neural network ensembles for outlier detection N Pawlowski, M Jaques, B Glocker arXiv preprint arXiv:1703.06749, 2017 | 7 | 2017 |
| Representation disentanglement for multi-task learning with application to fetal ultrasound Q Meng, N Pawlowski, D Rueckert, B Kainz Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image …, 2019 | 6 | 2019 |
| GainForest: Scaling Climate Finance for Forest Conservation using Interpretable Machine Learning on Satellite Imagery D Dao, C Cang, C Fung, M Zhang, N Pawlowski, R Gonzales, N Beglinger, ... ICML Climate Change AI workshop, 2019 | 5 | 2019 |
| Is Texture Predictive for Age and Sex in Brain MRI? N Pawlowski, B Glocker arXiv preprint arXiv:1907.10961, 2019 | 4 | 2019 |
| Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty M Monteiro, LL Folgoc, DC de Castro, N Pawlowski, B Marques, ... arXiv preprint arXiv:2006.06015, 2020 | 2 | 2020 |
Ben GlockerImperial College LondonVerified email at imperial.ac.uk
