26 citations · 38 across the 5 of their papers we have counts for
4 papers · 1 filter
A Process for the Evaluation of Node Embedding Methods in the Context of Node Classification
Christoph Martin, Meike Riebeling
Node embedding methods find latent lower-dimensional representations which are used as features in machine learning models. In the last few years, these methods have become extreme…
The impact of partially missing communities~on the reliability of centrality measures
Christoph Martin
Network data is usually not error-free, and the absence of some nodes is a very common type of measurement error. Studies have shown that the reliability of centrality measures is…
Estimating the sensitivity of centrality measures w.r.t. measurement errors
Christoph Martin, Peter Niemeyer
Most network studies rely on an observed network that differs from the underlying network which is obfuscated by measurement errors. It is well known that such errors can have a se…
Comparing the sensitivity of social networks, web graphs, and random graphs with respect to vertex removal
Christoph Martin, Peter Niemeyer
The sensitivity of networks regarding the removal of vertices has been studied extensively within the last 15 years. A common approach to measure this sensitivity is (i) removing s…