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Enhancing Attribute-driven Fraud Detection with Risk-aware Graph Representation
Credit card fraud is a severe issue that causes significant losses for both cardholders and issuing banks. Existing methods utilize …
Sheng Xiang, Guibin Zhang, Dawei Cheng, Ying Zhang
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Enhancing Attribute-driven Fraud Detection with Risk-aware Graph Representation
Scalable Learning-Based Community-Preserving Graph Generation
Graph generation plays an essential role in understanding the formation of complex network structures across various fields, such as …
Sheng Xiang, Chenhao Xu, Dawei Cheng, Ying Zhang
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Scalable Learning-Based Community-Preserving Graph Generation
Generative Artificial Intelligence Model for Multi-granularity Power Data Simulation
Electric power resources are essential for the efficient and orderly development of society. Accurate power load forecasting is a key …
Yiwen Jiang, Sheng Xiang, Yihan Dai, Dawei Cheng
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Generative Artificial Intelligence Model for Multi-granularity Power Data Simulation
Graph neural networks for financial fraud detection: a review
The landscape of financial transactions has grown increasingly complex due to the expansion of global economic integration and …
Dawei Cheng, Yao Zou, Sheng Xiang, Changjun Jiang
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Graph neural networks for financial fraud detection: a review
Parallel Graph Learning with Temporal Stamp Encoding for Fraudulent Transactions Detections
Financial transaction systems have become the critical backbone of modern society, and the sharp increase in fraudulent transactions …
Jiacheng Ma, Sheng Xiang, Qiang Li, Liangyu Yuan, Dawei Cheng, Changjun Jiang
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Parallel Graph Learning with Temporal Stamp Encoding for Fraudulent Transactions Detections
MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU
As financial markets grow increasingly complex in the big data era, accurate stock prediction has become more critical. Traditional …
Peng Zhu, Yuante Li, Yifan Hu, Sheng Xiang, Qinyuan Liu, Dawei Cheng, Yuqi Liang
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MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU
Anti-Money Laundering by Group-Aware Deep Graph Learning
Anti-money laundering (AML) is a classical data mining problem in finance applications. As well known, money laundering (ML) is …
Dawei Cheng, Yujia Ye, Sheng Xiang, Zhenwei Ma, Ying Zhang, Changjun Jiang
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Anti-Money Laundering by Group-Aware Deep Graph Learning
Financial time series forecasting with multi-modality graph neural network
Financial time series analysis plays a central role in hedging market risks and optimizing investment decisions. This is a challenging …
Dawei Cheng, Fangzhou Yang, Sheng Xiang, Jin Liu
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Financial time series forecasting with multi-modality graph neural network
General graph generators: experiments, analyses, and improvements
Graph simulation is one of the most fundamental problems in graph processing and analytics. It can help users to generate new graphs on …
Sheng Xiang, Dong Wen, Dawei Cheng, Ying Zhang, Lu Qin, Zhengping Qian, Xuemin Lin
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General graph generators: experiments, analyses, and improvements
Efficient top-k vulnerable nodes detection in uncertain graphs
Uncertain graphs have been widely used to model complex linked data in many applications, such as guaranteed-loan networks and power …
Dawei Cheng, Chen Chen, Xiaoyang Wang, Sheng Xiang
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Efficient top-k vulnerable nodes detection in uncertain graphs