14 citations · 14 across the 3 of their papers we have counts for
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stat.ML2018
Explaining Machine Learning Models using Entropic Variable Projection
François Bachoc, Fabrice Gamboa, Max Halford +2
In this paper, we present a new explainability formalism designed to shed light on how each input variable of a test set impacts the predictions of machine learning models. Hence,…
stat.ME2018
Gaussian processes with multidimensional distribution inputs via optimal transport and Hilbertian embedding
Francois Bachoc, Alexandra Suvorikova, David Ginsbourger +2
In this work, we investigate Gaussian Processes indexed by multidimensional distributions. While directly constructing radial positive definite kernels based on the Wasserstein dis…