35 citations · 46 across the 6 of their papers we have counts for
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cs.LG2024★ 4 cited
Learned feature representations are biased by complexity, learning order, position, and more
Andrew Kyle Lampinen, Stephanie C. Y. Chan, Katherine Hermann
Representation learning, and interpreting learned representations, are key areas of focus in machine learning and neuroscience. Both fields generally use representations as a means…
cs.LG2023★ 6 cited
On the Foundations of Shortcut Learning
Katherine L. Hermann, Hossein Mobahi, Thomas Fel +1
Deep-learning models can extract a rich assortment of features from data. Which features a model uses depends not only on \emph{predictivity} -- how reliably a feature indicates tr…