5 papers
Counterfactual Identifiability via Dynamic Optimal Transport
Fabio De Sousa Ribeiro, Ainkaran Santhirasekaram, Ben Glocker
We address the open question of counterfactual identification for high-dimensional multivariate outcomes from observational data. Pearl (2000) argues that counterfactuals must be i…
CF-Seg: Counterfactuals meet Segmentation
Raghav Mehta, Fabio De Sousa Ribeiro, Tian Xia +4
Segmenting anatomical structures in medical images plays an important role in the quantitative assessment of various diseases. However, accurate segmentation becomes significantly…
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Avinash Kori, Francesco Locatello, Ainkaran Santhirasekaram +3
Learning modular object-centric representations is crucial for systematic generalization. Existing methods show promising object-binding capabilities empirically, but theoretical i…
Vector Quantisation for Robust Segmentation
Ainkaran Santhirasekaram, Avinash Kori, Mathias Winkler +2
The reliability of segmentation models in the medical domain depends on the model's robustness to perturbations in the input space. Robustness is a particular challenge in medical…
Hierarchical Symbolic Reasoning in Hyperbolic Space for Deep Discriminative Models
Ainkaran Santhirasekaram, Avinash Kori, Andrea Rockall +3
Explanations for \emph{black-box} models help us understand model decisions as well as provide information on model biases and inconsistencies. Most of the current explainability t…