Differentially private synthetic data generation offers a recent solution to release analytically useful while preserving the privacy of individuals in data. In order utilize these algorithms for public policy decisions, policymakers need an accurate understanding algorithms' comparative performance. Correspondingly, practitioners also require standard metrics evaluating analytic qualities this...

One goal of metabolic engineering and synthetic biology for cyanobacteria and microalgae is to engineer strains that can optimally produce biofuels and commodity chemicals. However, the current workflow is slow and labor intensive with respect to assembly of genetic parts and characterization of production yields because of the slow growth rates of these organisms. Here, we review recent progre...

We present here results of audio-visual to articulatory inversion for French fricatives embedded into VCVs. The inversion technique is evaluated using both experimental and synthetic data. The final synthesis is assessed by a perceptual categorisation test. Synthetic stimuli have similar scores as natural ones.

Abstract Synthetic data is a rapidly evolving field with growing interest from multiple industry stakeholders and European bodies. In particular, the pharmaceutical starting to realise value of synthetic which being utilised more prevalently as method optimise utility sharing, ultimately an innovative response demand for improved privacy. generated by simulation, based upon mirroring properties...

This short paper provides a synthesis of the statistical disclosure limitation and computer science data privacy approaches to measuring the confidentiality protections provided by fully synthetic data. Since all elements of the data records in the release file derived from fully synthetic data are sampled from an appropriate probability distribution, they do not represent “real data,” but ther...