555 citations · 2.9k across the 55 of their papers we have counts for
4 papers · 1 filter
Network Inference from Consensus Dynamics with Unknown Parameters
Yu Zhu, Michael T. Schaub, Ali Jadbabaie +1
We explore the problem of inferring the graph Laplacian of a weighted, undirected network from snapshots of a single or multiple discrete-time consensus dynamics, subject to parame…
Graph-based Semi-Supervised & Active Learning for Edge Flows
Junteng Jia, Michael T. Schaub, Santiago Segarra +1
We present a graph-based semi-supervised learning (SSL) method for learning edge flows defined on a graph. Specifically, given flow measurements on a subset of edges, we want to pr…
Blind identification of stochastic block models from dynamical observations
Michael T. Schaub, Santiago Segarra, John N. Tsitsiklis
We consider a blind identification problem in which we aim to recover a statistical model of a network without knowledge of the network's edges, but based solely on nodal observati…
Spectral partitioning of time-varying networks with unobserved edges
Michael T. Schaub, Santiago Segarra, Hoi-To Wai
We discuss a variant of `blind' community detection, in which we aim to partition an unobserved network from the observation of a (dynamical) graph signal defined on the network. W…