Nick Pawlowski
Nick Pawlowski
Senior Researcher, Microsoft Research
Verified email at - Homepage
Cited by
Cited by
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
Rasa: Open source language understanding and dialogue management
T Bocklisch, J Faulkner, N Pawlowski, A Nichol
arXiv preprint arXiv:1712.05181, 2017
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
Deep structural causal models for tractable counterfactual inference
N Pawlowski, D Coelho de Castro, B Glocker
Advances in neural information processing systems 33, 857-869, 2020
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
Implicit weight uncertainty in neural networks
N Pawlowski, A Brock, MCH Lee, M Rajchl, B Glocker
arXiv preprint arXiv:1711.01297, 2017
Does your dermatology classifier know what it doesn’t know? detecting the long-tail of unseen conditions
AG Roy, J Ren, S Azizi, A Loh, V Natarajan, B Mustafa, N Pawlowski, ...
Medical Image Analysis 75, 102274, 2022
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
Stochastic segmentation networks: Modelling spatially correlated aleatoric uncertainty
M Monteiro, L Le Folgoc, D Coelho de Castro, N Pawlowski, B Marques, ...
Advances in neural information processing systems 33, 12756-12767, 2020
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
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
Automating morphological profiling with generic deep convolutional networks
N Pawlowski, JC Caicedo, S Singh, AE Carpenter, A Storkey
BioRxiv, 085118, 2016
Unsupervised lesion detection in brain CT using bayesian convolutional autoencoders
N Pawlowski, MCH Lee, M Rajchl, S McDonagh, E Ferrante, K Kamnitsas, ...
Deep end-to-end causal inference
T Geffner, J Antoran, A Foster, W Gong, C Ma, E Kiciman, A Sharma, ...
arXiv preprint arXiv:2202.02195, 2022
CytoGAN: generative modeling of cell images
P Goldsborough, N Pawlowski, JC Caicedo, S Singh, AE Carpenter
BioRxiv, 227645, 2017
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
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
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
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
K Dvijotham, J Winkens, M Barsbey, S Ghaisas, R Stanforth, N Pawlowski, ...
Nature Medicine 29 (7), 1814-1820, 2023
Understanding causality with large language models: Feasibility and opportunities
C Zhang, S Bauer, P Bennett, J Gao, W Gong, A Hilmkil, J Jennings, C Ma, ...
arXiv preprint arXiv:2304.05524, 2023
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