18 citations · 21 across the 4 of their papers we have counts for
4 papers
Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions
Huiqi Deng, Na Zou, Mengnan Du +5
Various attribution methods have been developed to explain deep neural networks (DNNs) by inferring the attribution/importance/contribution score of each input variable to the fina…
A General Taylor Framework for Unifying and Revisiting Attribution Methods
Huiqi Deng, Na Zou, Mengnan Du +3
Attribution methods provide an insight into the decision-making process of machine learning models, especially deep neural networks, by assigning contribution scores to each indivi…
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution
Huiqi Deng, Na Zou, Weifu Chen +3
Back propagation based visualizations have been proposed to interpret deep neural networks (DNNs), some of which produce interpretations with good visual quality. However, there ex…
A Unified Taylor Framework for Revisiting Attribution Methods
Huiqi Deng, Na Zou, Mengnan Du +3
Attribution methods have been developed to understand the decision-making process of machine learning models, especially deep neural networks, by assigning importance scores to ind…