… We conclude with the role of quantum measurement and the role of human consciousness
… Formally, a neural network can be considered as a directed graph mapping the N inputs of …

… It is customary to represent a commercial network in the form of a directed graph, where
the … For simplicity, we use relative units of measurement, which will expand the scope of the …

… We then introduce a topology-based similarity measure for population coactivity that is
sensitive to invariant stimulus structure and show that this measure captures invariant neural …

… In this entry, we focus on their recent application to the area of search engines, namely, the
PageRank algorithm employed at Google, which provides a measure of importance for each …

Within the conventional statistical physics framework, we study critical phenomena in
configuration network models with hidden variables controlling links between pairs of nodes. We …

… The Levenshtein distance is a string metric for measuring the difference between two …
These are mostly directed graphs, with nodes and links containing specific domain-related …

… configurations, we propose a new metric𝑇𝐶 to measure the total time cost of each kind of …
Though our solution can be easily extended to process directed graphs, vertex/edge labels …

… box so that the large-scale set of describing equations can be replaced by a much smaller
set of analogous equations without sacrificing the accuracy of the input-to-output behavior. …