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Found 4 papers, 3 papers with code
Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms
However, a single metric is not sufficient to fully capture the differences between DLP algorithms, and is prone to overly optimistic performance evaluation.
Gaussian Embedding of Temporal Networks
Representing the nodes of continuous-time temporal graphs in a low-dimensional latent space has wide-ranging applications, from prediction to visualization.
New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs
We leverage these visualization tools to investigate the effect of negative sampling on the predictive performance, at the node and edge level.
Graph-Survival: A Survival Analysis Framework for Machine Learning on Temporal Networks
Continuous time temporal networks are attracting increasing attention due their omnipresence in real-world datasets and they manifold applications.
