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  2. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    Another inspiration for GANs was noise-contrastive estimation, [113] which uses the same loss function as GANs and which Goodfellow studied during his PhD in 2010–2014. Adversarial machine learning has other uses besides generative modeling and can be applied to models other than neural networks.

  3. Wasserstein GAN - Wikipedia

    en.wikipedia.org/wiki/Wasserstein_GAN

    The Wasserstein Generative Adversarial Network (WGAN) is a variant of generative adversarial network (GAN) proposed in 2017 that aims to "improve the stability of learning, get rid of problems like mode collapse, and provide meaningful learning curves useful for debugging and hyperparameter searches".

  4. StyleGAN - Wikipedia

    en.wikipedia.org/wiki/StyleGAN

    The Style Generative Adversarial Network, or StyleGAN for short, is an extension to the GAN architecture introduced by Nvidia researchers in December 2018, [1] and made source available in February 2019.

  5. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    A generative AI system is constructed by applying unsupervised machine learning (invoking for instance neural network architectures such as generative adversarial networks (GANs), variation autoencoders (VAEs), transformers, or self-supervised machine learning trained on a dataset.

  6. Inception score - Wikipedia

    en.wikipedia.org/wiki/Inception_score

    The Inception Score (IS) is an algorithm used to assess the quality of images created by a generative image model such as a generative adversarial network (GAN). [1] The score is calculated based on the output of a separate, pretrained Inception v3 image classification model applied to a sample of (typically around 30,000) images generated by the generative model.

  7. Wait, exactly how many people work for the federal government?

    www.aol.com/wait-exactly-many-people-federal...

    A version of this story appeared in CNN’s What Matters newsletter. To get it in your inbox, sign up for free here.. The US grew a lot in the past 40 years.

  8. Adversarial machine learning - Wikipedia

    en.wikipedia.org/wiki/Adversarial_machine_learning

    Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. [1] A survey from May 2020 exposes the fact that practitioners report a dire need for better protecting machine learning systems in industrial applications.

  9. Vitamin D not recommended for preventing fractures in older ...

    www.aol.com/vitamin-d-not-recommended-preventing...

    The U.S. Preventive Services Task Force released a draft recommendation advising against using vitamin D to prevent falls and fractures in people over 60. Pharmacist Katy Dubinsky weighs in.