换句话说,做一个attribution,就是过一遍反向传播。 Integrated Gradient IG其实就是vanilla gradient上了一个小trick。vanilla有一个致命问题:当输入特征的值很小时,梯度反而大;当输入特征的值很大时,梯度反而小。因此,对于输入特征值很大的情况,由于输出对输入的梯度变成0,我们很自然地发现原始的saliency map方法输出...
The gradient-based formulation generalizes the method to other architectures but does not guarantee meaningful results outside the scope DeepLIFT was designed for. 2. In fact, \(\epsilon \)-LRP and DeepLIFT (Rescale) are not implementation invariant so the result might change depending on the ...
The goal of an attribution method is to determine a real value R(x_i) for each input feature, with respect to a target neuron of interest (for example, the activation of the neuron corresponsing to the correct class). When the attributions of all input features are arranged together to ...
Consider a network and a specific input to this network (eg. an image, if the network is trained for image classification). The input is multi-dimensional, made of several features. In the case of images, each pixel can be considered a feature. The goal of an attribution method is to ...
The method we have developed for endocardial and epicardial contours detection is based on the use of texture analysis and active contours models. Texture analysis allows us to define energy maps more efficient than those usually used in active contours methods where attractor is often based on ...
Newton’s method’s guiding principles serve as the basis for the traditional GBO31. To solve the deterministic issue, the MOIGBO’s efficiency has been contrasted to that of MOGBO and multi-objective particle swarm optimization (MOPSO). Paper’s organization “Methodology” section of the ensuin...
This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Nita C, Vandewalle S, Meyers J. On the efficiency of gradient based opti- mization algorithms for DNS-based...
The method considers two assumptions, so that the model described by Equation (1) can be linearized dynamically [7]: Assumption 1: The partial derivatives of 𝑓(⋯)f⋯ with respect to all variables are continuous for all 𝑘k with finite exceptions. Assumption 2: The system (1) satisf...
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Share and Cite MDPI and ACS Style Liu, G.; Li, M.; Zhang, W.; Gu, J. Subpixel Matching Using Double-...
Therefore, Lundberg and Lee (2017a) recently developed SHAP (Shapley Additive exPlanations), an additive feature attribution method, which they showed has a unique solution in the class of explanation models aimed at post-hoc interpreting machine learning methods, and which is more aligned with ...