A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)
Hi, let's say I have a simple MLP with 6 layers :
First layer : 2539 neurones
Second layer : 4564 neurones
Third layer : 4519 neurones
Fourth layer : 2141 neurones
Fifth layer : 383 neurones
Last layer : 2 neurones
How can i get the relevance score for each layer in this format : (x_exemple_length,nb_neurones) ?
Hi, let's say I have a simple MLP with 6 layers : First layer : 2539 neurones Second layer : 4564 neurones Third layer : 4519 neurones Fourth layer : 2141 neurones Fifth layer : 383 neurones Last layer : 2 neurones How can i get the relevance score for each layer in this format : (x_exemple_length,nb_neurones) ?