Alternatives and similar repositories for synthetic_data_generation:

Users that are interested in synthetic_data_generation are comparing it to the libraries listed below

• alan-turing-institute / QUIPP-pipeline
  Privacy preserving synthetic data generation workflows
  ☆20Updated 3 years ago
• alan-turing-institute / tapas
  ☆35Updated last year
• Baukebrenninkmeijer / On-the-Generation-and-Evaluation-of-Synthetic-Tabular-Data-using-GANs
  Repository for the results of my master thesis, about the generation and evaluation of synthetic data using GANs
  ☆44Updated last year
• Pushkar-v / Generating-Synthetic-Data-using-GANs
  Generating Tabular Synthetic Data using State of the Art GAN architecture
  ☆79Updated 4 years ago
• Baukebrenninkmeijer / table-evaluator
  Evaluate real and synthetic datasets against each other
  ☆86Updated last month
• sunchang0124 / dp_cgans
  A library to generate synthetic tabular or RDF data using Conditional Generative Adversary Networks (GANs) combined with Differential Pri…
  ☆37Updated 4 months ago
• BorealisAI / private-data-generation
  A toolbox for differentially private data generation
  ☆129Updated last year
• spring-epfl / synthetic_data_release
  ☆39Updated 2 years ago
• DPBayes / twinify
  A software package for privacy-preserving generation of a synthetic twin to a given sensitive data set.
  ☆51Updated 5 months ago
• astorfi / cor-gan
  COR-GAN: Correlation-Capturing Convolutional Neural Networks for Generating Synthetic Healthcare Records
  ☆57Updated 4 years ago
• yknot / ESANN2019
  Supplemental Material for the ESANN 2019 Submission "Preserving privacy using synthetic data models and applications in health informatic…
  ☆19Updated 4 years ago
• SelfExplainML / Aletheia
  A Python package for unwrapping ReLU DNNs
  ☆70Updated last year
• IFCA-Advanced-Computing / pycanon
  pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.
  ☆30Updated this week
• theodi / synthetic-data-tutorial
  A hands-on tutorial showing how to use Python to do anonymisation with synthetic data
  ☆78Updated 2 years ago
• charliemarx / pmtools
  ☆9Updated 4 years ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆36Updated 3 years ago
• mlhcmit / recitations
  Here we will post recitation materials.
  ☆9Updated 5 years ago
• PracticalFairness / BookRepo
  ☆14Updated 4 years ago
• donalee / DualAAE-EHR
  Dual Adversarial Autoencoder for Generating Set-valued Sequences
  ☆18Updated 4 years ago
• stefanrmmr / differentially_private_synthetic_data
  Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS
  ☆11Updated 2 years ago
• charmlab / mace
  Model Agnostic Counterfactual Explanations
  ☆86Updated 2 years ago
• usnistgov / SDNist
  SDNist: Benchmark data and evaluation tools for data synthesizers.
  ☆34Updated last week
• interpretml / FasterRisk
  Create sparse and accurate risk scoring systems!
  ☆35Updated 6 months ago
• interpretml / gam-changer
  Editing machine learning models to reflect human knowledge and values
  ☆124Updated last year
• leriomaggio / privacy-preserving-data-science
  Course Material for the Tutorial on Privacy Enhancing Technologies and PPML
  ☆12Updated 3 years ago
• Lory94 / dp-GAN
  Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data
  ☆33Updated 6 years ago
• jli0117 / ehrMGAN
  code for ehrMGAN
  ☆19Updated 2 years ago
• ustunb / risk-slim
  simple customizable risk scores in python
  ☆136Updated last year
• yubin-park / hcuppy
  A Python implementation of the tools from H-CUP (Healthcare Cost and Utilization Project)
  ☆63Updated last year
• dylan-slack / Fooling-LIME-SHAP
  Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
  ☆82Updated 2 years ago