Graph-Based Similarity of Neural Network Representations. (arXiv:2111.11165v2 [cs.LG] UPDATED)

Understanding the black-box representations in Deep Neural Networks (DNN) is
an essential problem in deep learning. In this work, we propose Graph-Based
Similarity (GBS) to measure the similarity of layer features. Contrary to
previous works that compute the similarity directly on the feature maps, GBS
measures the correlation based on the graph constructed with hidden layer
outputs. By treating each input sample as a node and the corresponding layer
output similarity as edges, we construct the graph of DNN representations …

arxiv graph graph-based network neural network