Search Results for author:
Found 6 papers, 0 papers with code
Granger-faithfulness and link orientation in network reconstruction
We formalize a variant of faithfulness for dynamic systems, called Granger-faithfulness, and for a large class of dynamic networks, we show that Granger-unfaithful systems constitute a Lebesgue zero-measure set.
An algorithm for reconstruction of triangle-free linear dynamic networks with verification of correctness
However, in many practical scenarios, strictly causal models are not adequate to describe the system and it is necessary to consider models with dynamics that include direct feedthrough terms.
An Algorithm to Learn Polytree Networks with Hidden Nodes
In this article, we develop an algorithm to exactly recover graphical models of random variables with underlying polytree structures when the latent nodes satisfy specific degree conditions.
Physics Informed Topology Learning in Networks of Linear Dynamical Systems
Learning influence pathways of a network of dynamically related processes from observations is of considerable importance in many disciplines.
Learning the Exact Topology of Undirected Consensus Networks
In this article, we present a method to learn the interaction topology of a network of agents undergoing linear consensus updates in a non invasive manner.
Exact Topology Reconstruction of Radial Dynamical Systems with Applications to Distribution System of the Power Grid
In this article we present a method to reconstruct the interconnectedness of dynamically related stochastic processes, where the interactions are bi-directional and the underlying topology is a tree.
