SynTPack

Tensorflow Implementation on "The Cramer Distance as a Solution to Biased Wasserstein Gradients" (https://arxiv.org/pdf/1705.10743.pdf)

SynDataGen is an advanced Python framework for generating and evaluating synthetic tabular datasets using modern generative models, including diffusion and adversarial architectures.

SynDataGen is an advanced Python framework for generating and evaluating synthetic tabular datasets using modern generative models, including diffusion and adversarial architectures.

NIST Collaborative Research Cycle on Synthetic Data. Learn about Synthetic Data week by week!

Credit Card Fraud Detection Project

Backtesting recommendations from Mad Money and "The Cramer Effect/Bounce"

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

The Anonymous Synthesizer for Health Data

This repository contains the code of our published work in IEEE JBHI. Our main objective was to demonstrate the feasibility of the use of synthetic data to effectively train Machine Learning algorithms, prooving that it benefits classification performance most of the times.

The following repository contains the online appendix for the paper "Generative AI for Banks: Benchmarks and Algorithms for Synthetic Financial Transaction Data". It not only provides the python code for all experiments conducted but also background information for the literature review.