2 citations · 4 across the 5 of their papers we have counts for
7 papers
Hyperbolic Latent Space Models for Network Embedding: Model Specification and Bayesian Inference
Yiwei Gong, Anna L. Smith, Dena Asta +1
Many real-world networks exhibit hierarchical, tree-like structure and heavy-tailed degree distributions, phenomena not readily captured by standard statistical models for network…
Prediction scoring of data-driven discoveries for reproducible research
Anna L. Smith, Tian Zheng, Andrew Gelman
Predictive modeling uncovers knowledge and insights regarding a hypothesized data generating mechanism (DGM). Results from different studies on a complex DGM, derived from differen…
Toward a Taxonomy of Trust for Probabilistic Machine Learning
Tamara Broderick, Andrew Gelman, Rachael Meager +2
Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. We need evidence to support that the resulting decisions are we…
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…
Diagnostics and Visualization of Point Process Models for Event Times on a Social Network
Jing Wu, Anna L. Smith, Tian Zheng
Point process models have been used to analyze interaction event times on a social network, in the hope to provides valuable insights for social science research. However, the diag…
The Geometry of Continuous Latent Space Models for Network Data
Anna L. Smith, Dena M. Asta, Catherine A. Calder
We review the class of continuous latent space (statistical) models for network data, paying particular attention to the role of the geometry of the latent space. In these models,…
Empirical Reference Distributions for Networks of Different Size
Anna Smith, Catherine A. Calder, Christopher R. Browning
Network analysis has become an increasingly prevalent research tool across a vast range of scientific fields. Here, we focus on the particular issue of comparing network statistics…