<ul><li>Researchers have introduced two novel approaches for releasing differentially private trace variants based on trained generative models.</li><li>The first approach, called TraVaG, utilizes Generative Adversarial Networks (GANs) to sample from a privatized implicit variant distribution.</li><li>The second approach employs Denoising Diffusion Probabilistic Models that reconstruct artificial trace variants from noise via trained Markov chains.</li><li>Both methods offer industry-scale benefits and elevate the degree of privacy assurances, particularly in scenarios featuring a substantial prevalence of infrequent variants.</li></ul>

Releasing Differentially Private Event Logs Using Generative Models

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