366 citations · 2.3k across the 53 of their papers we have counts for
54 papers
Non-Markovian epidemic spreading on temporal networks
Lilei Han, Zhaohua Lin, Qingqing Yin +3
Many empirical studies have revealed that the occurrences of contacts associated with human activities are non-Markovian temporal processes with a heavy tailed inter-event time dis…
Identifying super-spreaders in information-epidemic coevolving dynamics on multiplex networks
Qi Zeng, Ying Liu, Ming Tang +1
Identifying super-spreaders in epidemics is important to suppress the spreading of disease especially when the medical resource is limited.In the modern society, the information on…
The relative importance of structure and dynamics on node influence in reversible spreading processes
Junyi Qu, Ming Tang, Ying Liu +1
The reversible spreading processes with repeated infection widely exist in nature and human society, such as gonorrhea propagation and meme spreading. Identifying influential sprea…
Identify Influential Spreaders in Asymmetrically Interacting Multiplex Networks
Qi Zeng, Ying Liu, Liming Pan +1
Identifying the most influential spreaders is important to understand and control the spreading process in a network. As many real-world complex systems can be modeled as multilaye…
Asymmetrically interacting dynamics with mutual confirmation from multi-source on multiplex networks
Jiaxing Chen, Ying Liu, Ming Tang +1
In the early stage of epidemics, individuals' determination on adopting protective measures, which can reduce their risk of infection and suppress disease spreading, is likely to d…
Learning epidemic threshold in complex networks by Convolutional Neural Network
Qi Ni, Jie Kang, Ming Tang +2
Deep learning has taken part in the competition since not long ago to learn and identify phase transitions in physical systems such as many body quantum systems, whose underlying l…