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20172021
most citedImproving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients

280 citations · 330 across the 5 of their papers we have counts for

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stat.ML2018

Human-in-the-Loop Interpretability Prior

Isaac Lage, Andrew Slavin Ross, Been Kim +2

We often desire our models to be interpretable as well as accurate. Prior work on optimizing models for interpretability has relied on easy-to-quantify proxies for interpretability…