Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups von Farhadyar, Kiana, Bonofiglio, Federico, Hackenberg, Maren, Behrens, Max, Zöller, Daniela, Binder, Harald

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A generalized machine‐learning aided method for targeted identification of industrial enzymes from metagenome: A xylanase temperature dependence case study von Foroozandeh Shahraki, Mehdi, Farhadyar, Kiana, Kavousi, Kaveh, Azarabad, Mohammad H., Boroomand, Amin, Ariaeenejad, Shohreh, Hosseini Salekdeh, Ghasem

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Medication Management Systems Using mHealth Technology, Review on References von Kiana Farhadyar, Reza Safdari

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User Goals Extraction for a mhealth-based Medication Management System for Individuals with Visual Impairment von Farhadyar, Kiana, Safdari, Reza, Beh-Pajooh, Ahmad

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Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups von Farhadyar, Kiana, Bonofiglio, Federico, Hackenberg, Maren, Zoeller, Daniela, Binder, Harald

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Adapting deep generative approaches for getting synthetic data with realistic marginal distributions von Farhadyar, Kiana, Bonofiglio, Federico, Zoeller, Daniela, Binder, Harald

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Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups von Farhadyar, Kiana, Bonofiglio, Federico, Hackenberg, Maren, Zoeller, Daniela, Binder, Harald

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Adapting deep generative approaches for getting synthetic data with realistic marginal distributions von Farhadyar, Kiana, Bonofiglio, Federico, Zoeller, Daniela, Binder, Harald

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