71 citations · 163 across the 15 of their papers we have counts for
Showing 2021 · cs.LGShow all
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cs.LG2021★ 9 cited
Explaining Latent Representations with a Corpus of Examples
Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie +1
Modern machine learning models are complicated. Most of them rely on convoluted latent representations of their input to issue a prediction. To achieve greater transparency than a…
cs.LG2021★ 26 cited
Explaining Time Series Predictions with Dynamic Masks
Jonathan Crabbé, Mihaela van der Schaar
How can we explain the predictions of a machine learning model? When the data is structured as a multivariate time series, this question induces additional difficulties such as the…