6 papers
CurvFlow-DTA: dual-graph discrete Ricci curvature flow for drug--target affinity prediction
Jicheng Ma, Yunyan Yang, Juan Zhao +1
Graph neural networks are widely used for drug--target affinity (DTA) prediction, and discrete Ricci curvature has recently been used to characterize molecular graph geometry. Exis…
Evolving edge weights via local entropy flow and cohesion flow on graphs
Juan Zhao, Jicheng Ma, Yunyan Yang +1
In this paper, we first propose two different quantities on graphs, namely local entropy and cohesion, then design two corresponding flows for edge weights: the local entropy flow…
An Efficient Entropy Flow on Weighted Graphs: Theory and Applications
Juan Zhao, Jicheng Ma, Yunyan Yang +1
We propose a novel entropy flow on weighted graphs, which provides a principled framework that characterizes the evolution of probability distributions over graph structures while…
Geometric Evolution Graph Convolutional Networks: Enhancing Graph Representation Learning via Ricci Flow
Jicheng Ma, Yunyan Yang, Juan Zhao +1
We introduce the Geometric Evolution Graph Convolutional Network (GEGCN), a novel framework that enhances graph representation learning through explicit modeling of geometric evolu…
Finding core subgraphs of directed graphs via discrete Ricci curvature flow
Juan Zhao, Jicheng Ma, Yunyan Yang +1
Ricci curvature and its associated flow offer powerful geometric methods for analyzing complex networks. While existing research heavily focuses on applications for undirected grap…
Core detection via Ricci curvature flows on weighted graphs
Juan Zhao, Jicheng Ma, Yunyan Yang +1
Graph Ricci curvature is crucial as it geometrically quantifies network structure. It pinpoints bottlenecks via negative curvature, identifies cohesive communities with positive cu…