MalDataGen is an advanced Python framework for generating and evaluating synthetic tabular datasets using modern generative models, including diffusion and adversarial architectures.
SyntheticOcean: Open-Source Library for Generating Synthetic Tabular Data + SynDataGen (Framework for Synthetic Data Generation)
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.
Sintetizador de Datos para generar datos sintéticos tabulares a partir de un CSV.
Reproducible entity-resolution pipeline for duplicate detection in TED procurement records and synthetic-data audit
🚀 Synthetic Data Generation for Dielectric Characterization using Machine Learning | TVAE & CTGAN for Data Augmentation in Sensor Applications
Source code for the BRACIS 2026 project: [ From Bias to Fairness: Can Synthetic Data Bridge the Gap in Tabular Machine Learning? ]
Generalized Automatic Pipeline for inspecting and fixing uncertainties in your data
Streamlining the process to generate synthetic data. Just focus on the data, not the code!
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