Lei Meng

Orcid: 0000-0002-8351-2954

Affiliations:
  • Qinghai Normal University, Xining, China


According to our database1, Lei Meng authored at least 15 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
Self-supervised hypergraph structure learning.
Artif. Intell. Rev., June, 2025

Graph neural link predictor based on cycle structure.
CAAI Trans. Intell. Technol., 2025

2024
DeepMCGCN: Multi-channel Deep Graph Neural Networks.
Int. J. Comput. Intell. Syst., December, 2024

Line graph contrastive learning for node classification.
J. King Saud Univ. Comput. Inf. Sci., 2024

GSGSL: Gravity-driven self-supervised graph structure learning.
Inf. Process. Manag., 2024

TP-GCL: graph contrastive learning from the tensor perspective.
Frontiers Neurorobotics, 2024

2023
A Graph Representation Learning Framework Predicting Potential Multivariate Interactions.
Int. J. Comput. Intell. Syst., December, 2023

GFNC: Unsupervised Link Prediction Based on Gravitational Field and Node Contraction.
IEEE Trans. Comput. Soc. Syst., August, 2023

A Novel Link Prediction Framework Based on Gravitational Field.
Data Sci. Eng., March, 2023

Applications of Teaching Based on Virtual Reality in Agro-Pastoralism Areas.
Int. J. Inf. Commun. Technol. Educ., 2023

Multi-scale Heterogeneous Graph Contrastive Learning<sup>*</sup>.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Three-Channel Graph Convolutional Network.
Proceedings of the 24th IEEE Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, 2022

A practical adversarial attack on Graph Neural Networks by attacking single node structure.
Proceedings of the 24th IEEE Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, 2022

2020
Hypernetwork Model Based on Logistic Regression.
Proceedings of the Big Data - 8th CCF Conference, 2020

2019
Link Prediction Based on Gravitational Field of Complex Network.
Proceedings of the 2019 IEEE Intl Conf on Dependable, 2019


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