20 citations · 97 across the 23 of their papers we have counts for
5 papers · 1 filter
The power of dynamic social networks to predict individuals' mental health
Shikang Liu, David Hachen, Omar Lizardo +3
Precision medicine has received attention both in and outside the clinic. We focus on the latter, by exploiting the relationship between individuals' social interactions and their…
Heterogeneous network approach to predict individuals' mental health
Shikang Liu, Fatemeh Vahedian, David Hachen +4
Depression and anxiety are critical public health issues affecting millions of people around the world. To identify individuals who are vulnerable to depression and anxiety, predic…
Graphlets versus node2vec and struc2vec in the task of network alignment
Shawn Gu, Tijana Milenkovic
Network embedding aims to represent each node in a network as a low-dimensional feature vector that summarizes the given node's (extended) network neighborhood. The nodes' feature…
Alignment of dynamic networks
Vipin Vijayan, Dominic Critchlow, Tijana Milenkovic
Networks can model real-world systems in a variety of domains. Network alignment (NA) aims to find a node mapping that conserves similar regions between compared networks. NA is ap…
SCOUT: simultaneous time segmentation and community detection in dynamic networks
Yuriy Hulovatyy, Tijana Milenkovic
Many evolving complex systems can be modeled via dynamic networks. An important problem in dynamic network research is community detection, which identifies groups of topologically…