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Realistic Synthetic Financial Transactions for Anti-Money Laundering Models Erik Altman
The UN estimates 2-5% of global GDP or $0.8 - $2.0 trillion dollars are laundered
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fd83f4e0dcaf1c64ea15bbb1695bb40f-Paper-Conference.pdf
RCM. Finally, we illustrate the power of this conciliatory perspective by pinpointing
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FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks
However, the cross-client edges naturally exist among clients.
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Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective Zihan Luo
GNNs to mitigate the bias as well as boost their utility in an end-to-end manner.
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D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion
This prevailing paradigm heavily relies on the out-of-distribution (OOD) effect to influence the model's prediction.
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