89 citations · 430 across the 37 of their papers we have counts for
5 papers · 1 filter
Principal Graph Encoder Embedding and Principal Community Detection
Cencheng Shen, Yuexiao Dong, Carey E. Priebe +3
In this paper, we introduce the concept of principal communities and propose a principal graph encoder embedding method that concurrently detects these communities and achieves ver…
Refined Graph Encoder Embedding via Self-Training and Latent Community Recovery
Cencheng Shen, Jonathan Larson, Ha Trinh +1
This paper introduces a refined graph encoder embedding method, enhancing the original graph encoder embedding through linear transformation, self-training, and hidden community re…
Discovering Communication Pattern Shifts in Large-Scale Labeled Networks using Encoder Embedding and Vertex Dynamics
Cencheng Shen, Jonathan Larson, Ha Trinh +3
Analyzing large-scale time-series network data, such as social media and email communications, poses a significant challenge in understanding social dynamics, detecting anomalies,…
Synergistic Graph Fusion via Encoder Embedding
Cencheng Shen, Carey E. Priebe, Jonathan Larson +1
In this paper, we introduce a method called graph fusion embedding, designed for multi-graph embedding with shared vertex sets. Under the framework of supervised learning, our meth…
Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection
Cencheng Shen, Youngser Park, Carey E. Priebe
In this paper, we introduce a novel and computationally efficient method for vertex embedding, community detection, and community size determination. Our approach leverages a norma…