Time-series Generative Adversarial Networks for Telecommunications Data Augmentation
Time- series Generative Adversarial Networks (TimeGAN) is proposed to overcome the GAN model’s insufficiency in producing synthetic samples that inherit the predictive ability of the original timeseries data. TimeGAN combines the unsupervised adversarial loss in the GAN framework with a supervised l...
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Format: | Others |
Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2021
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Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303494 |