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  2. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.

  3. Variational autoencoder - Wikipedia

    en.wikipedia.org/wiki/Variational_autoencoder

    In addition to being seen as an autoencoder neural network architecture, variational autoencoders can also be studied within the mathematical formulation of variational Bayesian methods, connecting a neural encoder network to its decoder through a probabilistic latent space (for example, as a multivariate Gaussian distribution) that corresponds ...

  4. Autokey cipher - Wikipedia

    en.wikipedia.org/wiki/Autokey_cipher

    However, examining the results can suggest locations of the key being properly aligned. In those cases, the resulting decrypted text is potentially part of a word. In this example, it is highly unlikely that dfl is the start of the original plaintext and so it is highly unlikely either that the first three letters of the key are THE. Examining ...

  5. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    One encoder-decoder block A Transformer is composed of stacked encoder layers and decoder layers. Like earlier seq2seq models, the original transformer model used an encoder-decoder architecture. The encoder consists of encoding layers that process all the input tokens together one layer after another, while the decoder consists of decoding ...

  6. Types of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Types_of_artificial_neural...

    Some artificial neural networks are adaptive systems and are used for example to model populations and environments, which constantly change. Neural networks can be hardware- (neurons are represented by physical components) or software-based (computer models), and can use a variety of topologies and learning algorithms.

  7. Reparameterization trick - Wikipedia

    en.wikipedia.org/wiki/Reparameterization_trick

    The reparameterization trick (aka "reparameterization gradient estimator") is a technique used in statistical machine learning, particularly in variational inference, variational autoencoders, and stochastic optimization.

  8. 8 Overlooked Ways To Fund Your Holiday Purchases

    www.aol.com/finance/8-overlooked-ways-fund...

    Sam’s Club, for example, has a Landry’s $100 email delivery gift card for $79.98, limit two per membership. The card can be used at a variety of restaurants including Landry’s Seafood, Chart ...

  9. Attention (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Attention_(machine_learning)

    Both encoder & decoder are needed to calculate attention. [42] Both encoder & decoder are needed to calculate attention. [48] Decoder is not used to calculate attention. With only 1 input into corr, W is an auto-correlation of dot products. w ij = x i x j. [49] Decoder is not used to calculate attention. [50]