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pro vyhledávání: '"Maazoun, Wissem"'
Autor:
Esmaeilpour, Mohammad, Chaalia, Nourhene, Abusitta, Adel, Devailly, Francois-Xavier, Maazoun, Wissem, Cardinal, Patrick
This paper introduces a novel generative adversarial network (GAN) for synthesizing large-scale tabular databases which contain various features such as continuous, discrete, and binary. Technically, our GAN belongs to the category of class-condition
Externí odkaz:
http://arxiv.org/abs/2205.11693
Autor:
Esmaeilpour, Mohammad, Chaalia, Nourhene, Abusitta, Adel, Devailly, Francois-Xavier, Maazoun, Wissem, Cardinal, Patrick
This paper introduces a bi-discriminator GAN for synthesizing tabular datasets containing continuous, binary, and discrete columns. Our proposed approach employs an adapted preprocessing scheme and a novel conditional term for the generator network t
Externí odkaz:
http://arxiv.org/abs/2111.06549
Autor:
Esmaeilpour, Mohammad, Chaalia, Nourhene, Abusitta, Adel, Devailly, Franşois-Xavier, Maazoun, Wissem, Cardinal, Patrick
Publikováno v:
In Pattern Recognition Letters July 2022 159:204-210
Publikováno v:
In Aerospace Science and Technology August 2017 67:327-342