Ben Glocker Professor in Machine Learning for Imaging
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Recent Papers

  • Roschewitz et al (2025) Robust image representations with counterfactual contrastive learning
  • Jones et al. (2025) Rethinking Fair Representation Learning for Performance-Sensitive Tasks
  • Kori et al. (2024) Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
  • Jones et al. (2024) A causal perspective on dataset bias in machine learning for medical imaging
  • Kori et al. (2024) Grounded Object-Centric Learning
  • Ng et al. (2023) Prospective implementation of AI-assisted screen reading to improve early detection of breast cancer
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bernhardt2022active

2022 (1)

  • Mélanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay, Active label cleaning for improved dataset quality under resource constraints, Nature Communications, 2022
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