1 citations · 1 across the 4 of their papers we have counts for
4 papers
Probability density estimation for sets of large graphs with respect to spectral information using stochastic block models
Daniel Ferguson, François G. Meyer
For graph-valued data sampled iid from a distribution , the sample moments are computed with respect to a choice of metric. In this work, we equip the set of graphs with the pse…
Theoretical analysis and computation of the sample Frechet mean for sets of large graphs based on spectral information
Daniel Ferguson, Francois G. Meyer
To characterize the location (mean, median) of a set of graphs, one needs a notion of centrality that is adapted to metric spaces, since graph sets are not Euclidean spaces. A stan…
Approximate Fréchet Mean for Data Sets of Sparse Graphs
Daniel Ferguson, François G. Meyer
To characterize the location (mean, median) of a set of graphs, one needs a notion of centrality that is adapted to metric spaces, since graph sets are not Euclidean spaces. A stan…
On the Number of Edges of the Frechet Mean and Median Graphs
Daniel Ferguson, Francois G. Meyer
The availability of large datasets composed of graphs creates an unprecedented need to invent novel tools in statistical learning for graph-valued random variables. To characterize…