8 citations · 15 across the 9 of their papers we have counts for
10 papers
Dynamic Latent Space Modeling of Inhomogeneous Poisson Network Processes with Applications to International Relations
Jie Jian, Jiguo Cao, Owen G. Ward
We study continuous-time relational event data, where time-stamped dyadic interactions reflect both individual node propensities and evolving relational proximity. We propose a dyn…
Estimating Complex Densities using Two-Stage Normalizing Flows
Roxana Darvishi, David C. Stenning, Ted von Hippel +1
In many scientific applications, the target probability distribution cannot be evaluated in closed form or sampled from directly. Instead, it can often be decomposed into multiple…
Evaluating Aggregated Relational Data Models with Simple Diagnostics
Ian Laga, Benjamin Vogel, Jieyun Wang +2
Aggregated Relational Data (ARD) contain summary information about individual social networks and are widely used to estimate social network characteristics and the size of populat…
Bayesian Modeling for Aggregated Relational Data: A Unified Perspective
Owen G. Ward, Anna L. Smith, Tian Zheng
Aggregated relational data is widely collected to study social networks, in fields such as sociology, public health and economics. Many of the successes of ARD inference have been…
Investigating Experiential Effects in Online Chess using a Hierarchical Bayesian Analysis
Adam Gee, Sydney O. Seese, James P. Curley +1
The presence or absence of winner-loser effects is a widely discussed phenomenon across both sports and psychology research. Investigation of such effects is often hampered by the…
Scalable Community Detection in Massive Networks Using Aggregated Relational Data
Timothy Jones, Owen G. Ward, Yiran Jiang +2
The mixed membership stochastic blockmodel (MMSB) is a popular Bayesian network model for community detection. Fitting such large Bayesian network models quickly becomes computatio…
Network Hawkes Process Models for Exploring Latent Hierarchy in Social Animal Interactions
Owen G. Ward, Jing Wu, Tian Zheng +2
Group-based social dominance hierarchies are of essential interest in animal behavior research. Studies often record aggressive interactions observed over time, and models that can…
Online Estimation and Community Detection of Network Point Processes for Event Streams
Guanhua Fang, Owen G. Ward, Tian Zheng
A common goal in network modeling is to uncover the latent community structure present among nodes. For many real-world networks, the true connections consist of events arriving as…
Next Waves in Veridical Network Embedding
Owen G. Ward, Zhen Huang, Andrew Davison +1
Embedding nodes of a large network into a metric (e.g., Euclidean) space has become an area of active research in statistical machine learning, which has found applications in natu…
Markov-Modulated Hawkes Processes for Sporadic and Bursty Event Occurrences
Jing Wu, Owen G. Ward, James Curley +1
Modeling event dynamics is central to many disciplines. Patterns in observed event arrival times are commonly modeled using point processes. Such event arrival data often exhibits…