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stat.ML2026
TopoFisher: Learning Topological Summary Statistics by Maximizing Fisher Information
Matteo Biagetti, Mathieu Carrière, Francesco Conti +3
Persistence diagrams provide stable, interpretable summaries of geometric and topological structure and are useful for simulation-based inference when low-order statistics miss key…
stat.ML2024
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks
Charles Arnal, Felix Hensel, Mathieu Carrière +4
Despite their successful application to a variety of tasks, neural networks remain limited, like other machine learning methods, by their sensitivity to shifts in the data: their p…