1 code implementation • 27 Jun 2023 • Fabio De Sousa Ribeiro, Tian Xia, Miguel Monteiro, Nick Pawlowski, Ben Glocker
We present a general causal generative modelling framework for accurate estimation of high fidelity image counterfactuals with deep structural causal models.
1 code implementation • 2 Mar 2023 • Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker
We present a general framework for evaluating image counterfactuals.
no code implementations • 3 Nov 2022 • Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker
In such settings, semi-supervised learning (SSL) attempts to leverage the abundance of unlabelled data to obtain more robust and reliable models.
no code implementations • 8 Aug 2022 • Margherita Rosnati, Eyal Soreq, Miguel Monteiro, Lucia Li, Neil S. N. Graham, Karl Zimmerman, Carlotta Rossi, Greta Carrara, Guido Bertolini, David J. Sharp, Ben Glocker
We compare the predictive power of our proposed features to the Marshall score, independently and when paired with classic TBI biomarkers.
1 code implementation • 25 May 2022 • James Langley, Miguel Monteiro, Charles Jones, Nick Pawlowski, Ben Glocker
In contrast, improving the model for the observational distribution is rarely considered and typically defaults to a pixel-wise independent categorical or normal distribution.
1 code implementation • 1 Sep 2021 • Melanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Imperfections in data annotation, known as label noise, are detrimental to the training of machine learning models and have an often-overlooked confounding effect on the assessment of model performance.
1 code implementation • NeurIPS 2020 • Miguel Monteiro, Loïc le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker
In image segmentation, there is often more than one plausible solution for a given input.
2 code implementations • 19 Jul 2018 • Miguel Monteiro, Mário A. T. Figueiredo, Arlindo L. Oliveira
In this paper, we test whether this algorithm, which was shown to improve semantic segmentation for 2D RGB images, is able to improve segmentation quality for 3D multi-modal medical images.