A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)
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Updated
Nov 22, 2019 - Python
A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)
PyTorch implementation of GAN-based text-to-speech synthesis and voice conversion (VC)
Repository for my 2018 summer internship at GDP Labs, Indonesia about Generative Adversarial Network
A GAN made Tensorflow that generates 128 x 128 pixels images
This repo implements a simple GAN with fc layers and trains it on MNIST
《对抗演化与合作跃升》大大简化了几十亿年来生命演化和几千年来人类社会变革中重要事件和关键节点的理解。其中包括真核生命的出现、多细胞生命的形成(寒武纪的秘密)、社会性动物的出现、人类的由来、人类社会的发展等。 它有助于理解所有人类社会中出现的重要事物的本质,包括宗教、法律、市场经济等。而民族之兴衰、帝国之国运、人类文明的兴亡也都能从中得到解释。
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