2 papers
stat.ML2024
Node Regression on Latent Position Random Graphs via Local Averaging
Martin Gjorgjevski, Nicolas Keriven, Simon Barthelmé +1
Node regression consists in predicting the value of a graph label at a node, given observations at the other nodes. To gain some insight into the performance of various estimators…
stat.ML2023
The Graphical Nadaraya-Watson Estimator on Latent Position Models
M. Gjorgjevski
Given a graph with a subset of labeled nodes, we are interested in the quality of the averaging estimator which for an unlabeled node predicts the average of the observations of it…