Information about Test

  1. Generative adversarial network

    aimlexchange.com/search/wiki/page/Generative_adversarial_network

    A generative adversarial network (GAN) is a class of machine learning systems invented by Ian Goodfellow and his colleagues in 2014. Two neural networks

  2. StyleGAN

    aimlexchange.com/search/wiki/page/StyleGAN

    StyleGAN is a novel generative adversarial network (GAN) introduced by Nvidia researchers in December 2018, and open sourced in February 2019. StyleGAN

  3. Generative model

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    potential samples of input variables. Generative adversarial networks are examples of this class of generative models, and are judged primarily by the

  4. Deepfake

    aimlexchange.com/search/wiki/page/Deepfake

    learning and involve training generative neural network architectures, such as autoencoders or generative adversarial networks (GANs). Deepfakes have garnered

  5. Generative design

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    testing environment or an artificial intelligence, for example a generative adversarial network. The designer learns to refine the program (usually involving

  6. Unsupervised learning

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    detection Local Outlier Factor Neural Networks Autoencoders Deep Belief Nets Hebbian Learning Generative adversarial networks Self-organizing map Approaches

  7. Generative systems

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    subsystems Generative adversarial network – Deep learning method Generative music Generative art Generative grammar – Theory in linguistics Generative science –

  8. Edmond de Belamy

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    Edmond de Belamy is a generative adversarial network portrait painting constructed in 2018 by Paris-based arts-collective Obvious. Printed on canvas, the

  9. Artificial neural network

    aimlexchange.com/search/wiki/page/Artificial_neural_network

    photo-real talking heads; competitive networks such as generative adversarial networks in which multiple networks (of varying structure) compete with each

  10. Human image synthesis

    aimlexchange.com/search/wiki/page/Human_image_synthesis

    In 2014 Ian Goodfellow et al. presented the principles of a generative adversarial network. GANs made the headlines in early 2018 with the deepfakes controversies

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