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  2. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  3. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of generative model for unsupervised learning , GANs have also proved useful for semi-supervised learning , [ 2 ] fully supervised ...

  4. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library , and later supporting more.

  5. Wasserstein GAN - Wikipedia

    en.wikipedia.org/wiki/Wasserstein_GAN

    The original GAN method is based on the GAN game, a zero-sum game with 2 players: generator and discriminator. The game is defined over a probability space (,,), The generator's strategy set is the set of all probability measures on (,), and the discriminator's strategy set is the set of measurable functions : [,].

  6. Fréchet inception distance - Wikipedia

    en.wikipedia.org/wiki/Fréchet_inception_distance

    The Fréchet inception distance (FID) is a metric used to assess the quality of images created by a generative model, like a generative adversarial network (GAN) [1] or a diffusion model. [ 2 ] [ 3 ] The FID compares the distribution of generated images with the distribution of a set of real images (a "ground truth" set).

  7. Flow-based generative model - Wikipedia

    en.wikipedia.org/wiki/Flow-based_generative_model

    A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.

  8. StyleGAN - Wikipedia

    en.wikipedia.org/wiki/StyleGAN

    A direct predecessor of the StyleGAN series is the Progressive GAN, published in 2017. [9]In December 2018, Nvidia researchers distributed a preprint with accompanying software introducing StyleGAN, a GAN for producing an unlimited number of (often convincing) portraits of fake human faces.

  9. Gan Quan - Wikipedia

    en.wikipedia.org/wiki/Gan_Quan

    Gan Quan (甘泉; born June 17, 1996) is a Chinese baseball pitcher who plays with the Sichuan Dragons in the China Baseball League. He currently plays with the Texas AirHogs of the American Association. [1] Gan represented China at the 2017 World Baseball Classic [2] and 2018 Asian Games. [3]