… by decomposing the network classification decision into contributions of its input elements.
Although our focus is on image classification, … Our method called deep Taylor decomposition …

… In this paper, we have addressed the question of explaining anomalies, by proposing a
deep Taylor decomposition of the one-class SVM. The method is applicable to a number of …

… Deep Taylor decomposition, an implementation of LRP by … It is for these reasons we choose
the deep Taylor method as … relevance from a deep Taylor explanation of an input video, fea…

… for the model decision. For better redistribution and explanation of the correlation
between the input and the final o utput, we fi rst im prove th e Deep Taylor Decomposition(DTD) …

… We first evaluate the explanations generated by LRP for individual classification decisions.
Then, we analyze the theoretical foundation of LRP, ie, Deep Taylor Decomposition and shed …

… Similar to us, [18] used Taylor decomposition to explain neural network decisions, but
only … Unlike other works, we expressly derived Taylor-CAM for the purpose of explaining …

… -based explanation technique that can explain the decisions of a variety … deep Taylor
decomposition and the propagation process can be interpreted as a succession of first-order Taylor …

… From several methods currently available generating heat maps 30,31,32,33,34 , we based
our proposed method on the deep Taylor decomposition (DTD) method 35 which is a special …

… are not enough for interpreting and explaining the individual decision outputs of a network.
… effective for understanding and interpreting the classification decisions made by a DCNN. …

… The propagation rules are derived from a Taylor decomposition performed at each unit of …
in Deep Taylor Decomposition [8]. The redistribution rules proportional decompose the …