A common network inference problem, arising from real-world data constraints, is how to
infer a dynamic network from its time-aggregated adjacency matrix and time-varying …

When collecting dynamic network data, it is often more admissible—either due to privacy
concerns or real-time feasibility—to collect the marginals of a network than its time-varying …

Pairwise comparison models have been widely used for utility evaluation and ranking
across various fields. The increasing scale of problems today underscores the need to …

We consider a covariate-assisted ranking model grounded in the Plackett--Luce framework.
Unlike existing works focusing on pure covariates or individual effects with fixed covariates …

In an interconnected world, effective policymaking increasingly relies on understanding
complex human networks, such as contact networks for pandemic response, supply chain …

Origin-destination matrices of traveller flows are a key ingredient to transport planning. In
public transport planning, most agencies conduct origin-destination surveys to extract line …