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  2. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    The encoder-decoder architecture, often used in natural language processing and neural networks, can be scientifically applied in the field of SEO (Search Engine Optimization) in various ways: Text Processing: By using an autoencoder, it's possible to compress the text of web pages into a more compact vector representation. This can help reduce ...

  3. Variational autoencoder - Wikipedia

    en.wikipedia.org/wiki/Variational_autoencoder

    The KL-D from the free energy expression maximizes the probability mass of the q-distribution that overlaps with the p-distribution, which unfortunately can result in mode-seeking behaviour. The "reconstruction" term is the remainder of the free energy expression, and requires a sampling approximation to compute its expectation value. [8]

  4. 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.

  5. Attention (machine learning) - Wikipedia

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

    2. encoder-decoder QKV 3. encoder-only dot product 4. encoder-only QKV 5. Pytorch tutorial 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 ...

  6. Transformer (deep learning architecture) - Wikipedia

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

    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 layers that iteratively process the encoder's output and the decoder's output tokens so far.

  7. List of open-source codecs - Wikipedia

    en.wikipedia.org/wiki/List_of_open-source_codecs

    Turing – A High Efficiency Video Coding (HEVC/H.265) encoder implemented by BBC Research. libaom – Reference implementation for the royalty free AV1 video coding format by AOMedia, inheriting technologies from VP9, Daala and Thor. Kvazaar – An academic open-source encoder based on the High Efficiency Video Coding (HEVC/H.265) standard.

  8. HandBrake - Wikipedia

    en.wikipedia.org/wiki/HandBrake

    HandBrake is a free and open-source transcoder for digital video files. It was originally developed in 2003 by Eric Petit to make ripping DVDs to a data storage device easier. [3]

  9. 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