This document discusses recent developments in using Layer-wise Relevance Propagation (LRP) to explain decisions made by neural networks.
... to deliver high explanation quality, and how LRP can be extended to handle a variety of machine learning scenarios beyond deep neural networks. For a ...
Jul 31, 2019 ， In this study, we propose using layer-wise relevance propagation (LRP) to visualize convolutional neural network decisions for AD based on MRI ...
We hypothesized that using LRP in a naive predictive model would enable us to uncover relevant image features that a trained CNN uses for decision-making. Since ...
The LRP Toolbox for Artificial Neural Networks (1.3.1) ... The Layer-wise Relevance Propagation (LRP) algorithm explains a classifer's prediction specific to a ...
Missing: best practice decisions
May 20, 2024 ， LRP is another popular method for interpreting deep neural networks. It attributes the prediction of the model to input features by propagating ...
May 31, 2022 ， Methods for Interpreting and Understanding Deep Neural Networks ... Towards Best Practice ...
Duration: 20:21
Posted: May 31, 2022
Duration: 20:21
Posted: May 31, 2022
Oct 15, 2021 ， Towards best practice in explaining neural network decisions with LRP. In: Proceedings of the 2020 International Joint Conference on Neural ...
The Layer-wise Relevance Propagation (LRP) algorithm explains a classifier's prediction specific to a given data point by attributing relevance scores to ...
Nov 7, 2022 ， The LRP method is widely used to explain outcome predictions of many DNN models such as Convolution Neural Network (CNN) and Recurrent Neural ...