Machine learningDeep learning / NLP / CV

Gated Recurrent Unit (GRU)

Gated Recurrent Unit (GRU), koji su predstavili Cho et al. 2014. godine, jeste pojednostavljena rekurentna neuronska mreža koja koristi dva naučena gejta — gejt za ažuriranje i gejt za resetovanje — da bi selektivno zadržala ili odbacila informacije tokom vremenskih koraka, omogućavajući efikasno modelovanje sekvenci sa manje parametara nego LSTM.

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Izvori

  1. Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014). Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. In Proceedings of EMNLP 2014, pp. 1724–1734. link
  2. Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014). Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. NIPS 2014 Deep Learning Workshop. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Gated Recurrent Unit (GRU). ScholarGate. https://scholargate.app/sr/deep-learning/gated-recurrent-unit

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ScholarGateGated Recurrent Unit (Gated Recurrent Unit (GRU)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/deep-learning/gated-recurrent-unit · Skup podataka: https://doi.org/10.5281/zenodo.20539026