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2020 – today
- 2024
[j6]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)- [c16]Jiaqi Zhang, Joel Jennings, Agrin Hilmkil, Nick Pawlowski, Cheng Zhang, Chao Ma:
Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention. ICML 2024 - [c15]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. MICCAI (3) 2024: 400-410 - [i27]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 abs/2402.06665 (2024) - [i26]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 abs/2406.12807 (2024) - 2023
- [c14]Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski:
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise. ICLR 2023 - [c13]Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker:
Measuring axiomatic soundness of counterfactual image models. ICLR 2023 - [c12]Fabio De Sousa Ribeiro, Tian Xia, Miguel Monteiro, Nick Pawlowski, Ben Glocker:
High Fidelity Image Counterfactuals with Probabilistic Causal Models. ICML 2023: 7390-7425 - [c11]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: 472-481 - [c10]Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong:
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. NeurIPS 2023 - [i25]Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker:
Measuring axiomatic soundness of counterfactual image models. CoRR abs/2303.01274 (2023) - [i24]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 abs/2304.05524 (2023) - [i23]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 abs/2305.03829 (2023) - [i22]Fabio De Sousa Ribeiro, Tian Xia, Miguel Monteiro, Nick Pawlowski, Ben Glocker:
High Fidelity Image Counterfactuals with Probabilistic Causal Models. CoRR abs/2306.15764 (2023) - [i21]Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong:
BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery. CoRR abs/2307.13917 (2023) - 2022
- [j5]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: 102274 (2022) - [j4]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) - [c9]Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker:
Deep Structural Causal Shape Models. ECCV Workshops (6) 2022: 400-432 - [c8]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 - [i20]Tomas Geffner, Javier Antorán, 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 abs/2202.02195 (2022) - [i19]James Langley, Miguel Monteiro, Charles Jones, Nick Pawlowski, Ben Glocker:
Structured Uncertainty in the Observation Space of Variational Autoencoders. CoRR abs/2205.12533 (2022) - [i18]Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker:
Deep Structural Causal Shape Models. CoRR abs/2208.10950 (2022) - [i17]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 abs/2208.12610 (2022) - [i16]Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski:
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise. CoRR abs/2210.14706 (2022) - 2021
- [j3]Xiaoran Chen, Nick Pawlowski, Ben Glocker, Ender Konukoglu:
Normative ascent with local gaussians for unsupervised lesion detection. Medical Image Anal. 74: 102208 (2021) - [i15]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 abs/2104.03829 (2021) - 2020
- [c7]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 - [c6]Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker:
Deep Structural Causal Models for Tractable Counterfactual Inference. NeurIPS 2020 - [i14]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 abs/2001.08957 (2020) - [i13]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 abs/2006.06015 (2020) - [i12]Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker:
Deep Structural Causal Models for Tractable Counterfactual Inference. CoRR abs/2006.06485 (2020)
2010 – 2019
- 2019
- [j2]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): 2596-2606 (2019) - [j1]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): 3409-3418 (2019) - [c5]Qingjie Meng, Nick Pawlowski, Daniel Rueckert, Bernhard Kainz:
Representation Disentanglement for Multi-task Learning with Application to Fetal Ultrasound. SUSI/PIPPI@MICCAI 2019: 47-55 - [c4]Xiaoran Chen, Nick Pawlowski, Ben Glocker, Ender Konukoglu:
Unsupervised Lesion Detection with Locally Gaussian Approximation. MLMI@MICCAI 2019: 355-363 - [i11]Nick Pawlowski, Ben Glocker:
Is Texture Predictive for Age and Sex in Brain MRI? CoRR abs/1907.10961 (2019) - [i10]Nick Pawlowski, Suvrat Bhooshan, Nicolas Ballas, Francesco Ciompi, Ben Glocker, Michal Drozdzal:
Needles in Haystacks: On Classifying Tiny Objects in Large Images. CoRR abs/1908.06037 (2019) - [i9]Qingjie Meng, Nick Pawlowski, Daniel Rueckert, Bernhard Kainz:
Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound. CoRR abs/1908.07885 (2019) - 2018
- [c3]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: 547-556 - [i8]Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews, Ben Glocker:
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines. CoRR abs/1806.04224 (2018) - [i7]Xiaoran Chen, Nick Pawlowski, Martin Rajchl, Ben Glocker, Ender Konukoglu:
Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging. CoRR abs/1806.05452 (2018) - 2017
- [c2]Nick Pawlowski, Miguel Jaques, Ben Glocker:
Efficient variational Bayesian neural network ensembles for outlier detection. ICLR (Workshop) 2017 - [c1]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: 450-462 - [i6]Nick Pawlowski, Miguel Jaques, Ben Glocker:
Efficient variational Bayesian neural network ensembles for outlier detection. CoRR abs/1703.06749 (2017) - [i5]Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski, Murray Shanahan:
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning. CoRR abs/1705.06769 (2017) - [i4]Nick Pawlowski, Martin Rajchl, Ben Glocker:
Implicit Weight Uncertainty in Neural Networks. CoRR abs/1711.01297 (2017) - [i3]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 abs/1711.01468 (2017) - [i2]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 abs/1711.06853 (2017) - [i1]Tom Bocklisch, Joey Faulkner, Nick Pawlowski, Alan Nichol:
Rasa: Open Source Language Understanding and Dialogue Management. CoRR abs/1712.05181 (2017)
Coauthor Index
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last updated on 2024-10-11 18:19 CEST by the dblp team
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