Publications and Conferences
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A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging
Charles Jones, Daniel C. Castro, Fabio De Sousa Riberio, Ozan Oktay, Melissa McCradden & Ben Glocker
Nature Machine Learning, 6, 138-146 (2024)Making Predictions Under Interventions: A Case Study from the PREDICT-CVD Cohort in New Zealand Primary Care
Lin, L., Poppe, K., Wood, A., Martin, G. P., Peek, N., & Sperrin, M.
Front. Epidemiol. 2024 Apr 3:4:1326306Fairtune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy Hospedales
The Twelfth International Conference on Learning Representations, 2024Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models
Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang
NeurIPS 2024Explaining Image Classifiers
Hana Chockler & Joseph Y. Halpern
21st International Conference on Principles of Knowledge Representation and Reasoning (KR’2024) -
High order expression dependencies finely resolve cryptic states and subtypes in single cell data
Abel Jansma, Yuelin Yao, Jareth Wolfe, Luigi Del Debbio, Sjoerd V Beentjes, Chris P Ponting and Ava Khamseh
Mol Syst Biol (2025)21: 173-207Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Charles Jones, Fabio de Sousa Ribeiro, Mélanie Roschewitz, Daniel C. Castro, Ben Glocker
ICLR 2025 -
Jose Benitez-Aurioles , Alice Joules, Irene Brusini, Niels Peek, Matthew Sperrin
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Avinash Kori, Francesco Locatello, Ainkaran Santhirasekaram, Francesca Toni, Ben Glocker, Fabio De Sousa Ribeiro
NeurIPS 2024Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models
Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang
NeurIPS 2024Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning
Stefan Pranger, Hana Chockler, Martin Tappler, Bettina Konighofger
NeurIPS 2024Interactive Molecular Causal Networks of Hypertension Using a Fast Machine Learning Algorithm
Jack Kelly, Xiaoguang Xu, James M. Eales, Bernard Keavney, Carlo Berzuini, Maciej Tomaszewski & Hui Guo
BMC Med Res Methodol.2024 Aug 2;24(1):168Bounding Causal Effects with Leaky Instruments
David S. Watson, Jordan Penn, Lee M. Gunderson, Gecia Bravo-Hermsdorff, Afsaneh Mastouri, Ricardo Silva
40th Conference on Uncertainty in Artificial Intelligence (UAI 2024)Structured Learning of Compositional Sequential Interventions
Jialin Yu, Andreas Koukorinis, Nicolò Colombo, Yuchen Zhu, Ricardo Silva
NeurIPS 2024Counterfactual Contrastive Learning: Robust Representations via Causal Image Synthesis
Melanie Roschewitz, Fabio De Sousa Ribeiro, Tian Xia, Galvin Khara, Ben Glocker
DEMI 2024. Lecture Notes in Computer Science, vol 15265. Spinger, ChamMitigating Attribute Amplification in Counterfactual Image Generation
Tian Xia, Mélanie Roschewitz, Fabio De Sousa Ribeiro, Charles Jones, Ben Glocker
MICCAI 2024. Lecture Notes in Computer Science, vol 15010. Springer, ChamFairtune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy Hospedales
The Twelfth International Conference on Learning Representations, 2024Causal Blind Spots when using Prediction Models for Treatment Decisions
Nan van Geloven, Ruth H Keogh, Wouter van Amsterdam, Giovanni Cinà, Jesse H. Krijthe, Niels Peek, Kim Luijken, Sara Magliacane, Paweł Morzywołek, Thijs van Ommen, Hein Putter, Matthew Sperrin, Junfeng Wang, Daniala L. Weir, Vanessa Didelez
2024Pragmatic Fairness: Developing Policies with Outcome Disparity Control
Gultchin, L., Guo, S., Malek, A., Chiappa, S., & Silva, R
3rd Conference on Causal Learning and ReasoningMaking Predictions Under Interventions: A Case Study from the PREDICT-CVD Cohort in New Zealand Primary Care
Lin, L., Poppe, K., Wood, A., Martin, G. P., Peek, N., & Sperrin, M.
Front. Epidemiol. 2024 Apr 3:4:1326306A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging
Charles Jones, Daniel C. Castro, Fabio De Sousa Riberio, Ozan Oktay, Melissa McCradden & Ben Glocker
Nature Machine Learning, 6, 138-146 (2024)Explaining Image Classifiers
Hana Chockler & Joseph Y. Halpern
21st International Conference on Principles of Knowledge Representation and Reasoning (KR’2024)