Topics similar to or like Long short-term memory

Artificial recurrent neural network (RNN) architecture used in the field of deep learning. Wikipedia

  • Recurrent neural network

    Class of artificial neural networks where connections between nodes form a directed graph along a temporal sequence. This allows it to exhibit temporal dynamic behavior. Wikipedia

  • Deep learning

    Part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Wikipedia

  • Neural network

    Network or circuit of neurons, or in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Either a biological neural network, made up of real biological neurons, or an artificial neural network, for solving artificial intelligence problems. Wikipedia

  • Artificial neural network

    Artificial neural networks (ANNs), usually simply called neural networks (NNs), are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Wikipedia

  • Autoencoder

    Type of artificial neural network used to learn efficient data codings in an unsupervised manner. Autoencoder is to learn a representation for a set of data, typically for dimensionality reduction, by training the network to ignore signal “noise”. Wikipedia

  • Jürgen Schmidhuber

    Computer scientist most noted for his work in the field of artificial intelligence, deep learning and artificial neural networks. Co-director of the Dalle Molle Institute for Artificial Intelligence Research in Manno, in the district of Lugano, in Ticino in southern Switzerland. Wikipedia

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    • Each OpenAI Five network contains a single layer with a 1024-unit LSTM that observes the current game state extracted from the Dota developer’s API.OpenAI Five-Wikipedia
    • Long short-term memory (LSTM) recurrent units are typically incorporated after the CNN to account for inter-frame or inter-clip dependencies.Convolutional neural network-Wikipedia
    • In other words, we build an NLG system by training a machine learning algorithm (often an LSTM) on a large data set of input data and corresponding (human-written) output texts.Natural-language generation-Wikipedia
    • Long short-term memory (LSTM) networks were invented by Hochreiter and Schmidhuber in 1997 and set accuracy records in multiple applications domains.Recurrent neural network-Wikipedia
    • Version 4 adds LSTM based OCR engine and models for many additional languages and scripts, bringing the total to 116 languages.Tesseract (software)-Wikipedia
    • There have been many methods developed to approach this problem, such as Long short-term memory units.History of artificial intelligence-Wikipedia

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