manik-marwaha / Predicting-fraudulent-transactions-in-cryptosLinks
using the Elliptic Data Set (https://www.kaggle.com/ellipticco/elliptic-data-set) and working to improve on the orignals results by Weber, Mark, et al. "Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial forensics." arXiv preprint arXiv:1908.02591 (2019). We use ML models such as SVM and Random Fores…
☆13Updated last year
Alternatives and similar repositories for Predicting-fraudulent-transactions-in-cryptos
Users that are interested in Predicting-fraudulent-transactions-in-cryptos are comparing it to the libraries listed below
Sorting:
- EvolveGCN applied to Elliptic dataset☆30Updated 3 years ago
- Graph Convolutional Network on data from Elliptic bitcoin dataset of transactions graph☆16Updated 5 years ago
- Easy implementations of GCN on Elliptic Datasets☆13Updated 4 years ago
- This repository contains the code used in the experimental setup of the paper 'Inductive Graph Representation Learning for Fraud Detectio…☆33Updated 2 years ago
- This is the repository for the collection of Graph Neural Network for Financial Technology.☆28Updated 3 years ago
- This is a tensorflow-keras implementation of our paper "Attention Based Dynamic Graph Learning Framework for Asset Pricing"☆14Updated 3 years ago
- Community Detection on Higher-Order Networks: Identifying Patterns in US Air Traffic☆17Updated 4 years ago
- Online-lending fraud detection with customers' sequential behavioral data (End-to-end ML and NLP project).☆19Updated 4 years ago
- A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X☆133Updated 3 years ago
- Anomaly detection algorithm for social networks using Graph Neural Networks by leveraging graph parameteres, between centrality, degree, …☆12Updated 5 years ago
- Anti Money Laundering Detection using Graph Attention Network☆53Updated last year
- DYnamic MOtif-NoDes (DYMOND) is a dynamic network generative model based on temporal motifs and node behavior.☆14Updated 2 years ago
- The source code of the paper "SHGNN: Structure-Aware Heterogeneous Graph Neural Network"☆14Updated 3 years ago
- ☆33Updated 5 years ago
- A PyTorch implementation of DeepFD (Deep Structure Learning for Fraud Detection)☆30Updated 4 years ago
- ☆10Updated 4 years ago
- Continuous-Time Link Prediction via Temporal Dependent Graph Neural Network☆26Updated 4 years ago
- ☆10Updated 3 years ago
- This repository builds an anti-money laundering scheme employing graph theory and social network analysis to detect the sophisticated lay…☆20Updated 6 years ago
- An Unsupervised Graph-based Toolbox for Fraud Detection☆131Updated 3 years ago
- Fraud detection using Graph Convolutional Networks☆12Updated 3 years ago
- Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs (IJCAI'19)☆20Updated 3 years ago
- 构建简单的知识图谱实例——公司股票数据☆9Updated 6 years ago
- ☆10Updated 3 years ago
- ☆39Updated 2 years ago
- Paper collection for graph based models in finance application☆106Updated 4 years ago
- ☆71Updated 2 years ago
- OCAN: One-Class Adversarial Nets for Fraud Detection☆24Updated 6 years ago
- Incremental vertex representation learning using random walks and skip-gram model.☆12Updated 6 years ago
- KDD'22 ''Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning''☆13Updated 2 years ago