3 papers
stat.ME2025
Common-Individual Embedding for Dynamic Networks with Temporal Group Structure
Hairi Bai, Xinyan Fan, Kuangnan Fang +1
We propose STANE (Shared and Time-specific Adaptive Network Embedding), a new joint embedding framework for dynamic networks that captures both stable global structures and localiz…
stat.ME2025
Transfer learning under latent space model
Kuangnan Fang, Ruixuan Qin, Xinyan Fan
Latent space model plays a crucial role in network analysis, and accurate estimation of latent variables is essential for downstream tasks such as link prediction. However, the lar…
stat.ME2025
Network Model Averaging Prediction for Latent Space Models by K-Fold Edge Cross-Validation
Yan Zhang, Jun Liao, Xinyan Fan +2
In complex systems, networks represent connectivity relationships between nodes through edges. Latent space models are crucial in analyzing network data for tasks like community de…