2 papers
cs.LG2023
Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups
Kiana Farhadyar, Federico Bonofiglio, Maren Hackenberg +2
In settings requiring synthetic data generation based on a clinical cohort, e.g., due to data protection regulations, heterogeneity across individuals might be a nuisance that we n…
stat.ML2021
Adapting deep generative approaches for getting synthetic data with realistic marginal distributions
Kiana Farhadyar, Federico Bonofiglio, Daniela Zoeller +1
Synthetic data generation is of great interest in diverse applications, such as for privacy protection. Deep generative models, such as variational autoencoders (VAEs), are a popul…