activity
20172025
most citedTemporal Gravity Model for Important Nodes Identification in Temporal Networks

26 citations · 34 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2025★ 7 cited

Towards Interpretable Drug-Drug Interaction Prediction: A Graph-Based Approach with Molecular and Network-Level Explanations

Mengjie Chen, Ming Zhang, Cunquan Qu

Drug-drug interactions (DDIs) represent a critical challenge in pharmacology, often leading to adverse drug reactions with significant implications for patient safety and healthcar…

cs.IT2025

Dynamic Layered Decoding Scheduling for LDPC Codes Aided by Check Node Unsatisfied Probabilities

Chenyuan Jia, Dongxu Chang, Ruiyuan Wang +3

This letter revisits update ordering in layered belief propagation (LBP) decoding of low-density parity-check (LDPC) codes. The closest probability-based schedule orders layers by…

cs.LG2025

Multi-Scale Harmonic Encoding for Feature-Wise Graph Message Passing

Longlong Li, Mengyang Zhao, Guanghui Wang +1

Most Graph Neural Networks (GNNs) propagate messages by treating node embeddings as holistic feature vectors, implicitly assuming uniform relevance across feature dimensions. This…

cs.LG2025

TGT: A Temporal Gating Transformer for Smartphone App Usage Prediction

Longlong Li, Cunquan Qu, Guanghui Wang

Accurately predicting smartphone app usage is challenging due to the sparsity and irregularity of user behavior, especially under cold-start and low-activity conditions. Existing a…

physics.soc-ph2023

The generation and regulation of public opinion on multiplex social networks

Zhong Zhang, Jian-liang Wu, Cun-quan Qu +1

The dissemination of information and the development of public opinion are essential elements of most social media platforms and are often described as distinct, man-made occurrenc…

physics.soc-ph2020★ 26 cited

Temporal Gravity Model for Important Nodes Identification in Temporal Networks

Jialin Bi, Ji Jin, Cunquan Qu +2

Identifying important nodes is one of the central tasks in network science, which is crucial for analyzing the structure of a network and understanding the dynamical processes on a…

physics.soc-ph2020

Efficient algorithm based on non-backtracking matrix for community detection in signed networks

Zhaoyue Zhong, Xiangrong Wang, Cunquan Qu +1

Community detection or clustering is a crucial task for understanding the structure of complex systems. In some networks, nodes are permitted to be linked by either "positive" or "…

physics.soc-ph2017★ 1 cited

Self-Avoiding Pruning Random Walk on Signed Network

Huijuan Wang, Cunquan Qu, Chongze Jiao +1

A signed network represents how a set of nodes are connected by two logically contradictory types of links: positive and negative links. In a signed products network, two products…