41 citations · 95 across the 19 of their papers we have counts for
6 papers · 1 filter
Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions
Yixuan He, Aaron Sandel, David Wipf +3
How can we identify groups of primate individuals which could be conjectured to drive social structure? To address this question, one of us has collected a time series of data for…
Split Conformal Prediction under Data Contamination
Jase Clarkson, Wenkai Xu, Mihai Cucuringu +2
Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable…
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian
Yixuan He, Michael Permultter, Gesine Reinert +1
Signed and directed networks are ubiquitous in real-world applications. However, there has been relatively little work proposing spectral graph neural networks (GNNs) for such netw…
DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time Series
Jase Clarkson, Mihai Cucuringu, Andrew Elliott +1
Generative models for network time series (also known as dynamic graphs) have tremendous potential in fields such as epidemiology, biology and economics, where complex graph-based…
Lead-lag detection and network clustering for multivariate time series with an application to the US equity market
Stefanos Bennett, Mihai Cucuringu, Gesine Reinert
In multivariate time series systems, it has been observed that certain groups of variables partially lead the evolution of the system, while other variables follow this evolution w…
DIGRAC: Digraph Clustering Based on Flow Imbalance
Yixuan He, Gesine Reinert, Mihai Cucuringu
Node clustering is a powerful tool in the analysis of networks. We introduce a graph neural network framework, named DIGRAC, to obtain node embeddings for directed networks in a se…