Nick Pawlowski

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 47

Top Topics

Hierarchical Reinforcement Learning

Image Segmentation

Medical Imaging

Top Venues

Medical Image Anal.

Publications

Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR (2024)
Joshua Durso-Finley, Berardino Barile, Jean-Pierre R. Falet, Douglas L. Arnold, Nick Pawlowski, Tal Arbel
Probabilistic Temporal Prediction of Continuous Disease Trajectories and Treatment Effects Using Neural SDEs. CoRR (2024)
Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)
Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. NeurIPS (2023)
Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong
BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery. CoRR (2023)
Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker
Measuring axiomatic soundness of counterfactual image models. CoRR (2023)
Fabio De Sousa Ribeiro, Tian Xia, Miguel Monteiro, Nick Pawlowski, Ben Glocker
High Fidelity Image Counterfactuals with Probabilistic Causal Models. CoRR (2023)
Fabio De Sousa Ribeiro, Tian Xia, Miguel Monteiro, Nick Pawlowski, Ben Glocker
High Fidelity Image Counterfactuals with Probabilistic Causal Models. ICML (2023)
Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker
Measuring axiomatic soundness of counterfactual image models. ICLR (2023)
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise. ICLR (2023)
Joshua Durso-Finley, Jean-Pierre R. Falet, Raghav Mehta, Douglas L. Arnold, Nick Pawlowski, Tal Arbel
Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. CoRR (2023)
Cheng Zhang, Stefan Bauer, Paul Bennett, Jiangfeng Gao, Wenbo Gong, Agrin Hilmkil, Joel Jennings, Chao Ma, Tom Minka, Nick Pawlowski, James Vaughan
Understanding Causality with Large Language Models: Feasibility and Opportunities. CoRR (2023)
Joshua Durso-Finley, Jean-Pierre R. Falet, Raghav Mehta, Douglas L. Arnold, Nick Pawlowski, Tal Arbel
Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. MICCAI (5) (2023)
Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker
Deep Structural Causal Shape Models. ECCV Workshops (6) (2022)
Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Simultaneous Missing Value Imputation and Structure Learning with Groups. NeurIPS (2022)
Wenbo Gong, Digory Smith, Zichao Wang, Craig Barton, Simon Woodhead, Nick Pawlowski, Joel Jennings, Cheng Zhang
Instructions and Guide: Causal Insights for Learning Paths in Education. CoRR (2022)
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zachary Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Gregory S. Corrado, Umesh Telang, Yun Liu, A. Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens
Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions. Medical Image Anal. 75 (2022)
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise. CoRR (2022)
James Langley, Miguel Monteiro, Charles Jones, Nick Pawlowski, Ben Glocker
Structured Uncertainty in the Observation Space of Variational Autoencoders. Trans. Mach. Learn. Res. 2022 (2022)
Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker
Deep Structural Causal Shape Models. CoRR (2022)
James Langley, Miguel Monteiro, Charles Jones, Nick Pawlowski, Ben Glocker
Structured Uncertainty in the Observation Space of Variational Autoencoders. CoRR (2022)
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. CoRR (2022)
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zachary Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Gregory S. Corrado, Umesh Telang, Yun Liu, A. Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions. CoRR (2021)
Xiaoran Chen, Nick Pawlowski, Ben Glocker, Ender Konukoglu
Normative ascent with local gaussians for unsupervised lesion detection. Medical Image Anal. 74 (2021)
Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. NeurIPS (2020)
Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. CoRR (2020)
Rujikorn Charakorn, Yuttapong Thawornwattana, Sirawaj Itthipuripat, Nick Pawlowski, Poramate Manoonpong, Nat Dilokthanakul
An Explicit Local and Global Representation Disentanglement Framework with Applications in Deep Clustering and Unsupervised Object Detection. CoRR (2020)
Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker
Deep Structural Causal Models for Tractable Counterfactual Inference. NeurIPS (2020)
Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker
Deep Structural Causal Models for Tractable Counterfactual Inference. CoRR (2020)
Xiaoran Chen, Nick Pawlowski, Ben Glocker, Ender Konukoglu
Unsupervised Lesion Detection with Locally Gaussian Approximation. MLMI@MICCAI (2019)
Qingjie Meng, Nick Pawlowski, Daniel Rueckert, Bernhard Kainz
Representation Disentanglement for Multi-task Learning with Application to Fetal Ultrasound. SUSI/PIPPI@MICCAI (2019)
Nick Pawlowski, Suvrat Bhooshan, Nicolas Ballas, Francesco Ciompi, Ben Glocker, Michal Drozdzal
Needles in Haystacks: On Classifying Tiny Objects in Large Images. CoRR (2019)
Matthew C. H. Lee, Kersten Petersen, Nick Pawlowski, Ben Glocker, Michiel Schaap
TeTrIS: Template Transformer Networks for Image Segmentation With Shape Priors. IEEE Trans. Medical Imaging 38 (11) (2019)
Qingjie Meng, Nick Pawlowski, Daniel Rueckert, Bernhard Kainz
Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound. CoRR (2019)
Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski, Murray Shanahan
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. 30 (11) (2019)
Nick Pawlowski, Ben Glocker
Is Texture Predictive for Age and Sex in Brain MRI? CoRR (2019)
Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews, Ben Glocker
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines. CoRR (2018)
Xiaoran Chen, Nick Pawlowski, Martin Rajchl, Ben Glocker, Ender Konukoglu
Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging. CoRR (2018)
Vanya V. Valindria, Nick Pawlowski, Martin Rajchl, Ioannis Lavdas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker
Multi-modal Learning from Unpaired Images: Application to Multi-organ Segmentation in CT and MRI. WACV (2018)
Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski, Murray Shanahan
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning. CoRR (2017)
Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. CoRR (2017)
Nick Pawlowski, Miguel Jaques, Ben Glocker
Efficient variational Bayesian neural network ensembles for outlier detection. CoRR (2017)
Nick Pawlowski, Miguel Jaques, Ben Glocker
Efficient variational Bayesian neural network ensembles for outlier detection. ICLR (Workshop) (2017)
Tom Bocklisch, Joey Faulkner, Nick Pawlowski, Alan Nichol
Rasa: Open Source Language Understanding and Dialogue Management. CoRR (2017)
Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. BrainLes@MICCAI (2017)
Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Martin Rajchl
DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images. CoRR (2017)
Nick Pawlowski, Martin Rajchl, Ben Glocker
Implicit Weight Uncertainty in Neural Networks. CoRR (2017)