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20182024
most citedRNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks

38 citations · 83 across the 6 of their papers we have counts for

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Showing 2018Show all

2 papers · 1 filter

cs.CV2018★ 27 cited

DeepMiner: Discovering Interpretable Representations for Mammogram Classification and Explanation

Jimmy Wu, Bolei Zhou, Diondra Peck +4

We propose DeepMiner, a framework to discover interpretable representations in deep neural networks and to build explanations for medical predictions. By probing convolutional neur…

cs.CV2018★ 11 cited

Expert identification of visual primitives used by CNNs during mammogram classification

Jimmy Wu, Diondra Peck, Scott Hsieh +6

This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms. We propose an expert-in-the-loop interpret…