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Long Short-Term Memory (LSTM)

Era: The Revival · 1990s–2010s

Sepp Hochreiter and Jürgen Schmidhuber proposed LSTM, a special type of RNN capable of learning long-term dependencies. LSTM achieved great success in speech recognition and language modeling.

Sepp Hochreiter & Jürgen Schmidhuber

Sources and support

  1. Long Short-Term Memory

    Neural Computation · Source type: paper

    The original 1997 architecture uses memory cells, input gates, and output gates.

    Published: ·Accessed:

  2. Learning to Forget: Continual Prediction with LSTM

    Neural Computation / PubMed · Source type: paper

    The later paper introduces the forget gate.

    Published: ·Accessed: