4 citations · 4 across the 3 of their papers we have counts for
4 papers
A Network Science Perspective on Evaluating Deep Graph Generative Models
Tianrui Mao, Abele Malan, Megha Khosla +2
Traditional network models from network science, such as the Erdos-Renyi and configuration models, generate random networks that reproduce few selected topological properties obser…
Estimating Nodal Spreading Influence Using Partial Temporal Network
Tianrui Mao, Shilun Zhang, Alan Hanjalic +1
Temporal networks, whose links are activated or deactivated over time, are used to represent complex systems such as social interactions or collaborations occurring at specific tim…
BCIM: Budget and capacity constrained influence maximization in multilayer networks
Su-Su Zhang, Chuang Liu, Huijuan Wang +2
Influence maximization (IM) seeks to identify a seed set that maximizes influence within a network, with applications in areas such as viral marketing, disease control, and politic…
Predicting Nodal Influence via Local Iterative Metrics
Shilun Zhang, Alan Hanjalic, Huijuan Wang
Nodal spreading influence is the capability of a node to activate the rest of the network when it is the seed of spreading. Combining nodal properties (centrality metrics) derived…