Publications (31)
Measuring axiomatic soundness of counterfactual image models
Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski +2
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
Deep Structural Causal Shape Models
Rajat Rasal, Daniel C. Castro, Nick Pawlowski +1
Towards Causal Foundation Model: on Duality between Causal Inference and Attention
Jiaqi Zhang, Joel Jennings, Agrin Hilmkil +3
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery
Yashas Annadani, Nick Pawlowski, Joel Jennings +3
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster +9
Needles in Haystacks: On Classifying Tiny Objects in Large Images
Nick Pawlowski, Suvrat Bhooshan, Nicolas Ballas +3
Implicit Weight Uncertainty in Neural Networks
Nick Pawlowski, Andrew Brock, Matthew C. H. Lee +2
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro +5
An Explicit Local and Global Representation Disentanglement Framework with Applications in Deep Clustering and Unsupervised Object Detection
Rujikorn Charakorn, Yuttapong Thawornwattana, Sirawaj Itthipuripat +3
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning
Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski +1
Deep Structural Causal Models for Tractable Counterfactual Inference
Nick Pawlowski, Daniel C. Castro, Ben Glocker
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante +8
High Fidelity Image Counterfactuals with Probabilistic Causal Models
Fabio De Sousa Ribeiro, Tian Xia, Miguel Monteiro +2
Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound
Qingjie Meng, Nick Pawlowski, Daniel Rueckert +1
Simultaneous Missing Value Imputation and Structure Learning with Groups
Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb +5
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise
Wenbo Gong, Joel Jennings, Cheng Zhang +1
Probabilistic Temporal Prediction of Continuous Disease Trajectories and Treatment Effects Using Neural SDEs
Joshua Durso-Finley, Berardino Barile, Jean-Pierre Falet +3
Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging
Xiaoran Chen, Nick Pawlowski, Martin Rajchl +2
DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images
Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee +4
Structured Uncertainty in the Observation Space of Variational Autoencoders
James Langley, Miguel Monteiro, Charles Jones +2
Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models
Joshua Durso-Finley, Jean-Pierre Falet, Raghav Mehta +3
The Essential Role of Causality in Foundation World Models for Embodied AI
Tarun Gupta, Wenbo Gong, Chao Ma +11
NeurIPS Competition Instructions and Guide: Causal Insights for Learning Paths in Education
Wenbo Gong, Digory Smith, Zichao Wang +5
Rasa: Open Source Language Understanding and Dialogue Management
Tom Bocklisch, Joey Faulkner, Nick Pawlowski +1
Efficient variational Bayesian neural network ensembles for outlier detection
Nick Pawlowski, Miguel Jaques, Ben Glocker
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi +18
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines
Martin Rajchl, Nick Pawlowski, Daniel Rueckert +2
Is Texture Predictive for Age and Sex in Brain MRI?
Nick Pawlowski, Ben Glocker
A Portable Diagnostic Device for Cardiac Magnetic Field Mapping
John W. Mooney, Shima Ghasemi-Roudsari, Edward Reade Banham +3
Understanding Causality with Large Language Models: Feasibility and Opportunities
Cheng Zhang, Stefan Bauer, Paul Bennett +8