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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. Self-supervised learning - Wikipedia

    en.wikipedia.org/wiki/Self-supervised_learning

    Autoencoders consist of an encoder network that maps the input data to a lower-dimensional representation (latent space), and a decoder network that reconstructs the input from this representation. The training process involves presenting the model with input data and requiring it to reconstruct the same data as closely as possible.

  5. Restricted Boltzmann machine - Wikipedia

    en.wikipedia.org/wiki/Restricted_Boltzmann_machine

    Diagram of a restricted Boltzmann machine with three visible units and four hidden units (no bias units) A restricted Boltzmann machine (RBM) (also called a restricted Sherrington–Kirkpatrick model with external field or restricted stochastic Ising–Lenz–Little model) is a generative stochastic artificial neural network that can learn a probability distribution over its set of inputs.

  6. 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 , [ 93 ] [ 94 ] [ 95 ] where the input and output are written sentences in two natural languages.

  7. US national security adviser Sullivan says Trump should like ...

    www.aol.com/news/us-national-security-adviser...

    The AUKUS nuclear-powered submarine partnership with Australia will benefit the United States and is the kind of "burden sharing" deal that President-elect Donald Trump has talked about, U.S ...

  8. Ozempic Users Are Noticing This Unwanted Side Effect As They ...

    www.aol.com/doctors-explain-lose-weight-ozempic...

    Losing weight on a GLP-1 can lead to muscle loss, research shows. Here, obseity experts share how to preserve your lean muscle while simultaneously losing fat.

  9. 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 ...