Lin Meng

Orcid: 0009-0005-3977-5641

Affiliations:
  • Florida State University, Tallahassee, FL, USA


According to our database1, Lin Meng authored at least 13 papers between 2019 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2023
Decoupling Graph Neural Network with Contrastive Learning for Fraud Detection.
Proceedings of the Database Systems for Advanced Applications, 2023

Location-Adaptive Generative Graph Augmentation for Fraud Detection.
Proceedings of the 5th IEEE International Conference on Cognitive Machine Intelligence, 2023

Generative Graph Augmentation for Minority Class in Fraud Detection.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Deoscillated Adaptive Graph Collaborative Filtering.
Proceedings of the Topological, 2022

Stage Evolving Graph Neural Network based Dynamic Recommendation with Life Cycles.
Proceedings of the International Joint Conference on Neural Networks, 2022

2020
Deoscillated Graph Collaborative Filtering.
CoRR, 2020

Scalable Heterogeneous Social Network Alignment through Synergistic Graph Partition.
Proceedings of the HT '20: 31st ACM Conference on Hypertext and Social Media, 2020

Discovering Localized Information for Heterogeneous Graph Node Representation Learning.
Proceedings of the 6th IEEE International Conference on Collaboration and Internet Computing, 2020

2019
GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation.
CoRR, 2019

Graph Neural Lasso for Dynamic Network Regression.
CoRR, 2019

IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification.
CoRR, 2019

Deep Heterogeneous Social Network Alignment.
Proceedings of the 2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI), 2019

LATTE: Application Oriented Social Network Embedding.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019


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