Nick Pawlowski
Title
Cited by
Cited by
Year
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
3792018
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
2382018
Rasa: Open source language understanding and dialogue management
T Bocklisch, J Faulkner, N Pawlowski, A Nichol
arXiv preprint arXiv:1712.05181, 2017
1362017
Implicit weight uncertainty in neural networks
N Pawlowski, A Brock, MCH Lee, M Rajchl, B Glocker
arXiv preprint arXiv:1711.01297, 2017
532017
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
482017
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
342019
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
332018
Unsupervised lesion detection in brain CT using bayesian convolutional autoencoders
N Pawlowski, MCH Lee, M Rajchl, S McDonagh, E Ferrante, K Kamnitsas, ...
292018
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
282018
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
212019
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
192018
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
152017
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
72019
Efficient variational Bayesian neural network ensembles for outlier detection
N Pawlowski, M Jaques, B Glocker
arXiv preprint arXiv:1703.06749, 2017
72017
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
62019
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
52019
Is Texture Predictive for Age and Sex in Brain MRI?
N Pawlowski, B Glocker
arXiv preprint arXiv:1907.10961, 2019
42019
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
22020
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