Regularized Generative Adversarial Network
نویسندگان
چکیده
We propose a framework for generating samples from probability distribution that differs the of training set. use an adversarial process simultaneously trains three networks, generator and two discriminators. refer to this new model as regularized generative network (RegGAN). evaluate RegGAN on synthetic dataset composed gray scale images we further show it can be used learn some pre-specified notions in topology (basic properties). The work is motivated by practical problems encountered while using methods art world.
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ژورنال
عنوان ژورنال: Social Science Research Network
سال: 2021
ISSN: ['1556-5068']
DOI: https://doi.org/10.2139/ssrn.3796240