Gretel Blog

Promising evidence that state-of-the-art synthetic data models can produce artificial versions of even highly dimensional and complex genomic and phenotypic data.

Use synthetic data to improve model accuracy for fraud, cyber security, or any classification task with an extremely limited minority class.

Synthetic data is algorithmically generated data that mirrors the statistical properties of the dataset it’s based on. Learn how to make high-quality synthetic data.

How to enable faster access to data for medical research with statistically accurate, equitable and private synthetic datasets.

Answers to some questions about synthetic data that audience members submitted during Gretel's talk at The Rise of Privacy Tech’s Data Privacy Week 2022 conference.

How to use Weights & Biases’ ML hyperparameter sweeps tool to optimize the accuracy of your synthetic data.

How to train a FastCUT GAN on public location data from a few cities to predict realistic e-bike locations across the world.

Today, we are thrilled to announce the general availability of Gretel's privacy engineering APIs and services.

How we generated high-quality synthetic time-series data for one of the largest financial institutions in the world.

The Gretel research team's favorite trends and takeaways from the NeurlPS 35th Annual Conference on Neural Information Processing Systems.

A look at how using Gretel’s Privacy Filters to immunize synthetic datasets against adversarial attacks can impact machine learning accuracy.

How synthetic data can help nonprofits improve their business operations and their impact on the people they serve.