TigerGraph-DevLabs / AMLSim_Python_Lab
☆10Updated 2 years ago
Alternatives and similar repositories for AMLSim_Python_Lab:
Users that are interested in AMLSim_Python_Lab are comparing it to the libraries listed below
- Multi-GNN architectures for Anti-Money Laundering.☆75Updated last year
- Jupyter notebooks for testing ML models☆21Updated 4 years ago
- Fraud detection in bank transactions using graph databases and machine learning.☆21Updated 5 years ago
- This repository contains the code used in the experimental setup of the paper 'Inductive Graph Representation Learning for Fraud Detectio…☆33Updated last year
- Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"☆35Updated last year
- Fraud detection with the Paysim financial dataset, Neo4j Graph Data Science, and Neo4j Bloom☆45Updated 7 months ago
- AML End to End Example☆54Updated 2 years ago
- Anti Money Laundering Detection using Graph Attention Network☆46Updated last year
- This repository builds an anti-money laundering scheme employing graph theory and social network analysis to detect the sophisticated lay…☆19Updated 5 years ago
- Chartalist.org. Sponsored by the Canadian NSERC Discovery Grant RGPIN-2020-05665: Data Science on Blockchain and the National Science Fou…☆33Updated last year
- GraphRAG on Neo4j by finetuning GNN+LLM☆27Updated last month
- EvolveGCN applied to Elliptic dataset☆29Updated 3 years ago
- Exploring Neo4j and Graph Data Science for Fraud Detection☆72Updated last year
- Knowledge Graph Embeddings (KGE) to implement Explainable Artificial Intelligence. As AI develops users must know how algorithms make the…☆11Updated 4 years ago
- Simulation framework for customs fraud detection using import declarations.☆30Updated 2 years ago
- ☆31Updated last year
- ☆21Updated last year
- Given an input graph (ArangoDB or PyG) it generates graph embeddings using Low-Code framework built on top of PyG.☆68Updated 10 months ago
- Colab implementation for Fraud Detection in Graph Neural Networks, based on Deep Graph Library (DGL) and PyTorch backend.☆40Updated 3 years ago
- Temporal-Dynamics Aware Adversarial Attacks on Discrete Time Dynamic Graph Models☆14Updated 6 months ago
- Listing the research works related to risk control based on GNN and its interpretability. 1. we can learn the application of GNN in risk …☆12Updated 3 years ago
- Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning with 1 dollar.☆59Updated last year
- GiGL is an open-source library for training and inference of Graph Neural Networks at very large (billion) scale.☆43Updated this week
- Materials for SDM 2023 tutorial: Augmentation Methods for Graph Learning☆21Updated 2 years ago
- Python package for utilizing TigerGraph Databases☆32Updated last week
- Multi-Graph Graph Attention Network (MG-GAT) from "Y. Leng, R. Ruiz, X. Dong, and A. Pentland, Interpretable Recommender System With Het…☆27Updated 3 years ago
- Implementation of "Just Balance GNN" for graph classification and node clustering from the paper "Simplifying Clusterings with Graph Neur…☆34Updated last week
- The data represents financial transactions -- bank transfers, purchases, credit card transactions, checks, etc. Most of the transactions…☆48Updated last year
- GDS Patient Journey Demo☆13Updated last year
- ☆27Updated 10 months ago