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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 machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling. [1] It is part of the families of probabilistic graphical models and variational Bayesian methods.

  4. 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 ...

  5. Types of artificial neural networks - Wikipedia

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

    Encoder–decoder frameworks are based on neural networks that map highly structured input to highly structured output. The approach arose in the context of machine translation , [ 97 ] [ 98 ] [ 99 ] where the input and output are written sentences in two natural languages.

  6. 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.

  7. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...

  8. Encoder - Wikipedia

    en.wikipedia.org/wiki/Encoder

    Audio encoder, converts digital audio to analog audio signals; Video encoder, converts digital video to analog video signals; Simple encoder, assigns a binary code to an active input line; Priority encoder, outputs a binary code representing the highest-priority active input; 8b/10b encoder, creates DC balance on a communication transmission line

  9. Absolute encoder - Wikipedia

    en.wikipedia.org/?title=Absolute_encoder&redirect=no

    This page was last edited on 17 January 2020, at 23:10 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.