From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data. - Daniel Coelho de Castro; Sebastian Nowozin (ECCV (2), 2018)

Semi-Supervised Learning via Compact Latent Space Clustering. - Konstantinos Kamnitsas; Daniel Coelho de Castro; Loïc Le Folgoc; Ian Walker; Ryutaro Tanno; Daniel Rueckert; Ben Glocker; Antonio Criminisi; Aditya V. Nori (ICML, 2018)

Nonparametric Density Flows for MRI Intensity Normalisation. - Daniel Coelho de Castro; Ben Glocker (MICCAI (1), 2018)

Bayesian Deep Learning for Accelerated MR Image Reconstruction. - Jo Schlemper; Daniel Coelho de Castro; Wenjia Bai; Chen Qin; Ozan Oktay; Jinming Duan 001; Anthony N. Price; Joseph V. Hajnal; Daniel Rueckert (MLMIR@MICCAI, 2018)

Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning. - Jo Schlemper; Ozan Oktay; Wenjia Bai; Daniel Coelho de Castro; Jinming Duan 001; Chen Qin; Joseph V. Hajnal; Daniel Rueckert (MICCAI (1), 2018)

Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model. - Daniel Coelho de Castro; Sebastian Nowozin (CoRR, 2018)

Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. - Loïc Le Folgoc; Daniel Coelho de Castro; Jeremy Tan; Bishesh Khanal; Konstantinos Kamnitsas; Ian Walker; Amir Alansary; Ben Glocker (IPMI, 2019)

Domain Generalization via Model-Agnostic Learning of Semantic Features. - Qi Dou 001; Daniel Coelho de Castro; Konstantinos Kamnitsas; Ben Glocker (NeurIPS, 2019)

Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects. - Ben Glocker; Robert Robinson; Daniel Coelho de Castro; Qi Dou 001; Ender Konukoglu (CoRR, 2019)

Causality matters in medical imaging. - Daniel Coelho de Castro; Ian Walker; Ben Glocker (CoRR, 2019)

Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. - Daniel Coelho de Castro; Jeremy Tan; Bernhard Kainz; Ender Konukoglu; Ben Glocker (J. Mach. Learn. Res., 2019)

Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. - Robert Robinson; Qi Dou 001; Daniel Coelho de Castro; Konstantinos Kamnitsas; Marius de Groot; Ronald M. Summers; Daniel Rueckert; Ben Glocker (MICCAI (7), 2020)

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)

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs. - Shruthi Bannur; Ozan Oktay; Melanie Bernhardt; Anton Schwaighofer; Rajesh Jena; Besmira Nushi; Sharan Wadhwani; Aditya V. Nori; Kal Natarajan; Shazad Ashraf; Javier Alvarez-Valle; Daniel C. Castro (CoRR, 2021)

Active label cleaning: Improving dataset quality under resource constraints. - Melanie Bernhardt; Daniel C. Castro; Ryutaro Tanno; Anton Schwaighofer; Kerem Can Tezcan; Miguel Monteiro; Shruthi Bannur; Matthew P. Lungren; Aditya V. Nori; Ben Glocker; Javier Alvarez-Valle; Ozan Oktay (CoRR, 2021)

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. - Benedikt Boecking; Naoto Usuyama; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Stephanie L. Hyland; Maria Wetscherek; Tristan Naumann; Aditya V. Nori; Javier Alvarez-Valle; Hoifung Poon; Ozan Oktay (ECCV (36), 2022)

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

Analysing the effectiveness of a generative model for semi-supervised medical image segmentation. - Margherita Rosnati; Fabio De Sousa Ribeiro; Miguel Monteiro; Daniel Coelho de Castro; Ben Glocker (ML4H@NeurIPS, 2022)

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. - Shruthi Bannur; Stephanie L. Hyland; Qianchu Liu; Fernando Pérez-García; Maximilian Ilse; Daniel C. Castro; Benedikt Boecking; Harshita Sharma; Kenza Bouzid; Anja Thieme; Anton Schwaighofer; Maria Wetscherek; et al. (CVPR, 2023)

Exploring the Boundaries of GPT-4 in Radiology. - Qianchu Liu; Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Maria Wetscherek; Robert Tinn; Harshita Sharma; Fernando Pérez-García; Anton Schwaighofer; Pranav Rajpurkar; Sameer Tajdin Khanna; et al. (EMNLP, 2023)

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

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging. - Charles Jones; Daniel C. Castro; Fabio De Sousa Ribeiro; Ozan Oktay; Melissa D. McCradden; Ben Glocker (CoRR, 2023)

MAIRA-1: A specialised large multimodal model for radiology report generation. - Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Mercy Ranjit; Anton Schwaighofer; Fernando Pérez-García; Valentina Salvatelli; Shaury Srivastav; Anja Thieme; Noel Codella; Matthew P. Lungren; et al. (CoRR, 2023)

MAIRA at RRG24: A specialised large multimodal model for radiology report generation. - Shaury Srivastav; Mercy Ranjit; Fernando Pérez-García; Kenza Bouzid; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Harshita Sharma; Maximilian Ilse; Valentina Salvatelli; Sam Bond-Taylor; Fabian Falck; et al. (BioNLP@ACL, 2024)

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. - Nur Yildirim; Hannah Richardson; Maria Teodora Wetscherek; Junaid Bajwa; Joseph Jacob; Mark Ames Pinnock; Stephen Harris; Daniel Coelho de Castro; Shruthi Bannur; Stephanie L. Hyland; Pratik Ghosh; Mercy Ranjit; et al. (CHI, 2024)

RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing. - Fernando Pérez-García; Sam Bond-Taylor; Pedro P. Sanchez; Boris van Breugel; Daniel C. Castro; Harshita Sharma; Valentina Salvatelli; Maria T. A. Wetscherek; Hannah Richardson; Matthew P. Lungren; Aditya V. Nori; Javier Alvarez-Valle; et al. (ECCV (12), 2024)

Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning. - Ahmed Abdulaal; Adamos Hadjivasiliou; Nina Montaña Brown; Tiantian He 002; Ayodeji Ijishakin; Ivana Drobnjak; Daniel C. Castro; Daniel C. Alexander (ICLR, 2024)

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models. - Harshita Sharma; Valentina Salvatelli; Shaury Srivastav; Kenza Bouzid; Shruthi Bannur; Daniel C. Castro; Maximilian Ilse; Sam Bond-Taylor; Mercy Prasanna Ranjit; Fabian Falck; Fernando Pérez-García; Anton Schwaighofer; et al. (ML4H@NeurIPS, 2024)

RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision. - Fernando Pérez-García; Harshita Sharma; Sam Bond-Taylor; Kenza Bouzid; Valentina Salvatelli; Maximilian Ilse; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Matthew P. Lungren; Maria Wetscherek; Noel Codella; et al. (CoRR, 2024)

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. - Anja Thieme; Abhijith Rajamohan; Benjamin Cooper; Heather Groombridge; Robert Simister; Barney Wong; Nicholas Woznitza; Mark Ames Pinnock; Maria Teodora Wetscherek; Cecily Morrison; Hannah Richardson; Fernando Pérez-García; et al. (CoRR, 2024)

MAIRA-2: Grounded Radiology Report Generation. - Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Anton Schwaighofer; Sam Bond-Taylor; Maximilian Ilse; Fernando Pérez-García; Valentina Salvatelli; Harshita Sharma; Felix Meissen; Mercy Ranjit; Shaury Srivastav; et al. (CoRR, 2024)

An X-Ray Is Worth 15 Features: Sparse Autoencoders for Interpretable Radiology Report Generation. - Ahmed Abdulaal; Hugo Fry; Nina Montaña Brown; Ayodeji Ijishakin; Jack Gao; Stephanie L. Hyland; Daniel C. Alexander; Daniel C. Castro (CoRR, 2024)

PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation. - Daniel C. Castro; Aurelia Bustos; Shruthi Bannur; Stephanie L. Hyland; Kenza Bouzid; Maria Teodora Wetscherek; M. Sánchez-Valverde; Lara Jaques-Pérez; Lourdes Pérez-Rodríguez; Kenji Takeda; José María Salinas; Javier Alvarez-Valle; et al. (CoRR, 2024)

Balancing Act: Diversity and Consistency in Large Language Model Ensembles. - Ahmed Abdulaal; Chen Jin; Nina Montaña Brown; Aryo Pradipta Gema; Daniel C. Castro; Daniel C. Alexander; Philip Alexander Teare; Tom Diethe; Dino Oglic; Amrutha Saseendran (ICLR, 2025)

Rethinking Fair Representation Learning for Performance-Sensitive Tasks. - Charles Jones; Fabio De Sousa Ribeiro; Mélanie Roschewitz; Daniel C. Castro; Ben Glocker (ICLR, 2025)

Exploring scalable medical image encoders beyond text supervision. - Fernando Pérez-García; Harshita Sharma; Sam Bond-Taylor; Kenza Bouzid; Valentina Salvatelli; Maximilian Ilse; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Matthew P. Lungren; Maria Teodora Wetscherek; Noel Codella; et al. (Nat. Mac. Intell., 2025)

Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation. - Jong Hak Moon; Geon Choi; Paloma Rabaey; Min Gwan Kim; Hyuk Gi Hong; Jung-Oh Lee; Hangyul Yoon; Eun Woo Doe; Jiyoun Kim; Harshita Sharma; Daniel C. Castro; Javier Alvarez-Valle; et al. (CoRR, 2025)

Insights into a radiology-specialised multimodal large language model with sparse autoencoders. - Kenza Bouzid; Shruthi Bannur; Felix Meissen; Daniel Coelho de Castro; Anton Schwaighofer; Javier Alvarez-Valle; Stephanie L. Hyland (CoRR, 2025)

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. - Anja Thieme; Abhijith Rajamohan; Benjamin Cooper; Heather Groombridge; Robert Simister; Barney Wong; Nicholas Woznitza; Mark A. Pinnock; Maria T. A. Wetscherek; Cecily Morrison; Hannah Richardson; Fernando Pérez-García; et al. (ACM Trans. Comput. Hum. Interact., 2025)