A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
EvoNet: A Neural Network for Predicting the Evolution of Dynamic Graphs
[article]
2020
arXiv
pre-print
Neural networks for structured data like graphs have been studied extensively in recent years. To date, the bulk of research activity has focused mainly on static graphs. However, most real-world networks are dynamic since their topology tends to change over time. Predicting the evolution of dynamic graphs is a task of high significance in the area of graph mining. Despite its practical importance, the task has not been explored in depth so far, mainly due to its challenging nature. In this
arXiv:2003.00842v1
fatcat:izakvtzharbufg6sztjlm7nsim