Bidirectional recurrent neural networks
id:
bidirectional-recurrent-neural-networks-195-3135579
title:
Bidirectional recurrent neural networks
text:
Bidirectional recurrent neural networks (BRNN) connect two hidden layers of opposite directions to the same output. With this form of generative deep learning, the output layer can get information from past (backwards) and future (forward) states simultaneously. Invented in 1997 by Schuster and Paliwal, BRNNs were introduced to increase the amount of input information available to the network. For example, multilayer perceptron (MLPs) and time delay neural network (TDNNs) have limitations on the
brand slug:
wiki
category slug:
encyclopedia
description:
Type of artificial neural network
original url:
https://en.wikipedia.org/wiki/Bidirectional_recurrent_neural_networks
date created:
date modified:
2023-07-24T22:47:47Z
main entity:
{"identifier":"Q25112138","url":"https://www.wikidata.org/entity/Q25112138"}
image:
fields total:
13
integrity:
14