Gretel Blog

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

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

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.

We explore the popular open-source package Optuna to demonstrate how you can optimize your model hyperparameters and build the best synthetic model possible.

This article clarifies some common misconceptions about differential privacy and what it guarantees.

Quickly and safely aggregate geolocation data for location density analysis using a hexagonal grid system.