IEEE

Rotation- and Permutation-Equivariant Quantum Graph Neural Network for 3D Graph Data

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
Frontiers

Symptom-level interactions between anxiety and internet addiction in Chinese adolescents: a large-scale network and residence difference analysis

Background: Anxiety and Internet addiction (IA) are prevalent and exhibit a strong correlation among adolescents. This study aimed to (a) identify key symptoms and relationships of the anxiety-IA ...
IEEE

A Graph Neural Network for Learning Beamforming in Pinching Antenna Systems (PASS)

Abstract: A Graph Neural Network (GNN) for learning beamforming in Pinching Antenna SyStems (PASS) is proposed, which is called GPASS. The GPASS is with a staged architecture, where the positions of ...
C&EN

A Learning Framework for Atomic-Level Polymer Structure Generation

School of Materials Science and Engineering, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, Georgia 30332, United States School of Computational Science and Engineering, Georgia Institute ...
C&EN

Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network

Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...