Super-Resolution Community Detection for Layer-Aggregated Multilayer Networks
Applied network science often involves preprocessing network data before applying a network-analysis method, and there is typically a theoretical disconnect between these steps. For example, it is common to aggregate time-varying network data into windows prior to analysis, and the trade-offs of thi...
Main Authors: | Taylor, Dane, Mucha, Peter J., Caceres, Rajmonda S. |
---|---|
Other Authors: | Lincoln Laboratory |
Format: | Article |
Language: | English |
Published: |
American Physical Society
2018
|
Online Access: | http://hdl.handle.net/1721.1/114446 |
Similar Items
-
Selective network discovery via deep reinforcement learning on embedded spaces
by: Morales, Peter, et al.
Published: (2021) -
Parallel super-resolution imaging
by: Yew, Elijah Y S, et al.
Published: (2019) -
Improved face mask detection with super-resolution techniques
by: Suresh, Prem Adithya
Published: (2021) -
Classifying The Shape Of Aggregate Using Hybrid Multilayered Perceptron Network.
by: Joret, Ariffuddin, et al.
Published: (2005) -
Ion Aggregation, Correlated Ion Transport and the Double Layer in Super-Concentrated Electrolytes
by: McEldrew, Michael
Published: (2025)