Motif distribution and function of sparse deep neural networks

arXiv:2403.00974v1 Announce Type: new
Abstract: We characterize the connectivity structure of feed-forward, deep neural networks (DNNs) using network motif theory. To address whether a particular motif distribution is characteristic of the training task, or function of the DNN, we compare the connectivity structure of 350 DNNs trained to simulate a bio-mechanical flight control system with different randomly initialized parameters. We develop and implement algorithms for counting second- and third-order motifs and calculate their significance using their Z-score. The DNNs are …

abstract arxiv bio connectivity cs.lg distribution dnn function motif network networks neural networks theory training type