Jonathan Crabbé
Jonathan Crabbé
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Latent Density Models for Uncertainty Categorization
We introduce DAUX, an interpretability framework to interpret model uncertainty.
Hao Sun
,
Boris van Breugel
,
Jonathan Crabbé
,
Nabeel Seedat
,
Mihaela van der Schaar
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Explaining Latent Representations with a Corpus of Examples
We introduce SimplEx, a case-based reasoning explanation method that permits to decompose latent representations with a corpus of example.
Jonathan Crabbé
,
Zhaozhi Qian
,
Fergus Imrie
,
Mihaela van der Schaar
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Explaining Time Series Predictions with Dynamic Masks
We introduce Dynamask, a perturbation-based feature importance method to explain the predictions of time series models.
Jonathan Crabbé
,
Mihaela van der Schaar
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Learning outside the black-box: the pursuit of interpretable models
We introduce Symbolic Pursuit, a new method for symbolic regression based on Meijer G-functions and the projection pursuit algorithm.
Jonathan Crabbé
,
Yao Zhang
,
William R. Zame
,
Mihaela van der Schaar
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