8 citations · 8 across the 5 of their papers we have counts for
3 papers · 1 filter
Scalable Subgraph Sampling via Resistance Curvature
Chaoqun Fei, Tinglve Zhou, Tianyong Hao +1
Subgraph sampling reduces the training cost of large-scale graph neural networks, but sampling criteria may overlook the geometric roles of edges. We propose a resistance-curvature…
Dynamic Graph Structure Learning via Resistance Curvature Flow
Chaoqun Fei, Huanjiang Liu, Tinglve Zhou +2
Geometric Representation Learning (GRL) aims to approximate the non-Euclidean topology of high-dimensional data through discrete graph structures, grounded in the manifold hypothes…
Efficient Curvature-aware Graph Network
Chaoqun Fei, Tinglve Zhou, Tianyong Hao +1
Graph curvature provides geometric priors for Graph Neural Networks (GNNs), enhancing their ability to model complex graph structures, particularly in terms of structural awareness…