This respository implements three models described in Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics. Models are applied to Elliptic Bitcoin dataset.
- GCN
- GCN with skip connection
- EvolveGCN
- tensorflow ==2.4.1
- numpy <= 1.19.5
See articles:
- Weber, Mark, et al. "Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial forensics." arXiv preprint arXiv:1908.02591 (2019).
- Pareja, Aldo, et al. "EvolveGCN: Evolving graph convolutional networks for dynamic graphs." Proceedings of the AAAI Conference on Artificial Intelligence.