Unlearning Comparator, a visual tool to compare machine unlearning
I built Unlearning Comparator, a visual analytics toolkit to help researchers and developers compare how different machine unlearning methods work. It provides a unified workflow to test for accuracy, efficiency, and privacy. You can check out the live demo linked in the post, and the source code is on GitHub: https://github.com/gnueaj/Machine-Unlearning-Comparator Our accompanying paper is currently under review at IEEE TVCG. Happy to answer any questions and would love to hear your feedback!
Unlearning Comparator, a visual tool to compare machine unlearning launched on July 7, 2025 with 40 votes, #607 of 9,223 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Unlearning Comparator is a visual analytics toolkit designed for researchers and developers to evaluate and compare different machine unlearning methods. It provides a unified workflow to test machine learning models across three key dimensions: accuracy, efficiency, and privacy. The tool helps users understand how various unlearning approaches perform and trade off against each other, with source code available on GitHub.
written from the facts on this page · September 2026
From the sources
Machine Unlearning Dashboard
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