5 papers
A Metric Space of Spatial Graphs: Two-Sample Testing, Data Depth, and Application to Cardiac Fibrosis
Anna Calissano, Arstanbek Okenov, Katja Zeppenfeld +1
Cardiac fibrosis reduces electrical conductivity and is a leading cause of arrhythmia. Arrhythmic waves typically rotate around non-conducting fibrotic patches, so the geometry and…
Barycentric subspace analysis of network-valued data
Elodie Maignant, Xavier Pennec, Alain Trouvé +1
Certain data are naturally modeled by networks or weighted graphs, be they biological networks or mobility networks. When there is no canonical labeling of the nodes across the dat…
Graph Counterfactual Explainable AI via Latent Space Traversal
Andreas Abildtrup Hansen, Paraskevas Pegios, Anna Calissano +1
Explaining the predictions of a deep neural network is a nontrivial task, yet high-quality explanations for predictions are often a prerequisite for practitioners to trust these mo…
Conformal Prediction Sets for Populations of Graphs
Anna Calissano, Matteo Fontana, Gianluca Zeni +1
The analysis of data such as graphs has been gaining increasing attention in the past years. This is justified by the numerous applications in which they appear. Several methods ar…
Interpreting Equivariant Representations
Andreas Abildtrup Hansen, Anna Calissano, Aasa Feragen
Latent representations are used extensively for downstream tasks, such as visualization, interpolation or feature extraction of deep learning models. Invariant and equivariant neur…