Prediction and inference in complex networks: A brief review and perspectives
Abstract
Abstract Inference and prediction are fundamental to the study of complex systems, where network data are often incomplete, inaccurate or obtained indirectly. In this paper, we review recent advances in network sampling and comparison, as well as in link prediction and network reconstruction from time series. We summarise key methodological developments and emerging approaches that integrate statistical and machine learning perspectives. We also outline promising research directions for enhancing the inference and prediction of complex networked systems.
Fields of Study & Subjects
Complex Network Analysis Techniques
Advanced Graph Neural Networks
Mental Health Research Topics
Publication details
- Journal / source
- Europhysics Letters (EPL)
- Publisher
- IOP Publishing
- Volume
- 153
- Issue
- 2
- Pages
- 21002–21002
- Publication date
- 1 January 2026