Efficient variational Bayesian neural network ensembles for outlier detection. - Nick Pawlowski; Miguel Jaques; Ben Glocker (ICLR (Workshop), 2017)

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. - Konstantinos Kamnitsas; Wenjia Bai; Enzo Ferrante; Steven McDonagh 001; Matthew Sinclair; Nick Pawlowski; Martin Rajchl; Matthew C. H. Lee; Bernhard Kainz; Daniel Rueckert; Ben Glocker (BrainLes@MICCAI, 2017)

Implicit Weight Uncertainty in Neural Networks. - Nick Pawlowski; Martin Rajchl; Ben Glocker (CoRR, 2017)

DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images. - Nick Pawlowski; Sofia Ira Ktena; Matthew C. H. Lee; Bernhard Kainz; Daniel Rueckert; Ben Glocker; Martin Rajchl (CoRR, 2017)

Rasa: Open Source Language Understanding and Dialogue Management. - Tom Bocklisch; Joey Faulkner; Nick Pawlowski; Alan Nichol (CoRR, 2017)

Multi-modal Learning from Unpaired Images: Application to Multi-organ Segmentation in CT and MRI. - Vanya V. Valindria; Nick Pawlowski; Martin Rajchl; Ioannis Lavdas; Eric O. Aboagye; Andrea G. Rockall; Daniel Rueckert; Ben Glocker (WACV, 2018)

NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines. - Martin Rajchl; Nick Pawlowski; Daniel Rueckert; Paul M. Matthews; Ben Glocker (CoRR, 2018)

Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging. - Xiaoran Chen; Nick Pawlowski; Martin Rajchl; Ben Glocker; Ender Konukoglu (CoRR, 2018)

Unsupervised Lesion Detection with Locally Gaussian Approximation. - Xiaoran Chen; Nick Pawlowski; Ben Glocker; Ender Konukoglu (MLMI@MICCAI, 2019)

Representation Disentanglement for Multi-task Learning with Application to Fetal Ultrasound. - Qingjie Meng; Nick Pawlowski; Daniel Rueckert; Bernhard Kainz (SUSI/PIPPI@MICCAI, 2019)

Is Texture Predictive for Age and Sex in Brain MRI? - Nick Pawlowski; Ben Glocker (CoRR, 2019)

Needles in Haystacks: On Classifying Tiny Objects in Large Images. - Nick Pawlowski; Suvrat Bhooshan; Nicolas Ballas; Francesco Ciompi; Ben Glocker; Michal Drozdzal (CoRR, 2019)

TeTrIS: Template Transformer Networks for Image Segmentation With Shape Priors. - Matthew C. H. Lee; Kersten Petersen; Nick Pawlowski; Ben Glocker; Michiel Schaap (IEEE Trans. Medical Imaging, 2019)

Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning. - Nat Dilokthanakul; Christos Kaplanis; Nick Pawlowski; Murray Shanahan (IEEE Trans. Neural Networks Learn. Syst., 2019)

Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. - Miguel Monteiro; Loïc Le Folgoc; Daniel Coelho de Castro; Nick Pawlowski; Bernardo Marques; Konstantinos Kamnitsas; Mark van der Wilk; Ben Glocker (NeurIPS, 2020)

Deep Structural Causal Models for Tractable Counterfactual Inference. - Nick Pawlowski; Daniel Coelho de Castro; Ben Glocker (NeurIPS, 2020)

An Explicit Local and Global Representation Disentanglement Framework with Applications in Deep Clustering and Unsupervised Object Detection. - Rujikorn Charakorn; Yuttapong Thawornwattana; Sirawaj Itthipuripat; Nick Pawlowski; Poramate Manoonpong; Nat Dilokthanakul (CoRR, 2020)

Normative ascent with local gaussians for unsupervised lesion detection. - Xiaoran Chen; Nick Pawlowski; Ben Glocker; Ender Konukoglu (Medical Image Anal., 2021)

Deep Structural Causal Shape Models. - Rajat Rasal; Daniel C. Castro; Nick Pawlowski; Ben Glocker (ECCV Workshops (6), 2022)

Simultaneous Missing Value Imputation and Structure Learning with Groups. - Pablo Morales-Alvarez; Wenbo Gong 001; Angus Lamb; Simon Woodhead 002; Simon Peyton Jones; Nick Pawlowski; Miltiadis Allamanis; Cheng Zhang 005 (NeurIPS, 2022)

Deep End-to-end Causal Inference. - Tomas Geffner; Javier Antorán; Adam Foster 001; Wenbo Gong 001; Chao Ma 019; Emre Kiciman; Amit Sharma 007; Angus Lamb; Martin Kukla; Nick Pawlowski; Miltiadis Allamanis; Cheng Zhang 005 (CoRR, 2022)

Instructions and Guide: Causal Insights for Learning Paths in Education. - Wenbo Gong 001; Digory Smith; Zichao Wang 001; Craig Barton; Simon Woodhead 002; Nick Pawlowski; Joel Jennings; Cheng Zhang 005 (CoRR, 2022)

Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions. - Abhijit Guha Roy; Jie Ren 006; Shekoofeh Azizi; Aaron Loh; Vivek Natarajan; Basil Mustafa; Nick Pawlowski; Jan Freyberg; Yuan Liu; Zachary Beaver; Nam Vo; Peggy Bui; et al. (Medical Image Anal., 2022)

Structured Uncertainty in the Observation Space of Variational Autoencoders. - James Langley; Miguel Monteiro; Charles Jones; Nick Pawlowski; Ben Glocker (Trans. Mach. Learn. Res., 2022)

Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise. - Wenbo Gong 001; Joel Jennings; Cheng Zhang 005; Nick Pawlowski (ICLR, 2023)

Measuring axiomatic soundness of counterfactual image models. - Miguel Monteiro; Fabio De Sousa Ribeiro; Nick Pawlowski; Daniel C. Castro; Ben Glocker (ICLR, 2023)

High Fidelity Image Counterfactuals with Probabilistic Causal Models. - Fabio De Sousa Ribeiro; Tian Xia; Miguel Monteiro; Nick Pawlowski; Ben Glocker (ICML, 2023)

Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. - Joshua Durso-Finley; Jean-Pierre R. Falet; Raghav Mehta; Douglas L. Arnold; Nick Pawlowski; Tal Arbel (MICCAI (5), 2023)

BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. - Yashas Annadani; Nick Pawlowski; Joel Jennings; Stefan Bauer; Cheng Zhang 005; Wenbo Gong 001 (NeurIPS, 2023)

Understanding Causality with Large Language Models: Feasibility and Opportunities. - Cheng Zhang 005; Stefan Bauer; Paul Bennett; Jiangfeng Gao; Wenbo Gong 001; Agrin Hilmkil; Joel Jennings; Chao Ma 019; Tom Minka; Nick Pawlowski; James Vaughan (CoRR, 2023)

BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery. - Yashas Annadani; Nick Pawlowski; Joel Jennings; Stefan Bauer; Cheng Zhang 005; Wenbo Gong 001 (CoRR, 2023)

Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention. - Jiaqi Zhang; Joel Jennings; Agrin Hilmkil; Nick Pawlowski; Cheng Zhang 005; Chao Ma 019 (ICML, 2024)

Probabilistic Temporal Prediction of Continuous Disease Trajectories and Treatment Effects Using Neural SDEs. - Joshua Durso-Finley; Berardino Barile; Jean-Pierre R. Falet; Douglas L. Arnold; Nick Pawlowski; Tal Arbel (MICCAI (3), 2024)

The Essential Role of Causality in Foundation World Models for Embodied AI. - Tarun Gupta 002; Wenbo Gong 001; Chao Ma 019; Nick Pawlowski; Agrin Hilmkil; Meyer Scetbon; Ade Famoti; Ashley Juan Llorens; Jianfeng Gao 001; Stefan Bauer; Danica Kragic; Bernhard Schölkopf; et al. (CoRR, 2024)

Deep End-to-end Causal Inference. - Tomas Geffner; Javier Antorán; Adam Foster 001; Wenbo Gong 001; Chao Ma 019; Emre Kiciman; Amit Sharma 007; Angus Lamb; Martin Kukla; Nick Pawlowski; Agrin Hilmkil; Joel Jennings; et al. (Trans. Mach. Learn. Res., 2024)