Results 241 to 250 of about 296,489 (278)

Biologically plausible gated recurrent neural networks for working memory and learning-to-learn. [PDF]

PLoS One
van den Berg AR, Roelfsema PR, Bohte SM.
europepmc   +1 more source

Confidence interval forecasting model of small watershed flood based on compound recurrent neural networks and Bayesian. [PDF]

PLoS One
Wang S, Xu O.
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Exploring a digital music teaching model integrated with recurrent neural networks under artificial intelligence. [PDF]

Sci Rep
Han Y.
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Directional hand movement can be classified from insular cortex SEEG signals using recurrent neural networks and high-gamma band features. [PDF]

Sci Rep
Shao X, Chung RS, Cavaleri JM, Del Campo-Vera RM, Parra M, Sundaram S, Zhang S, Surabhi A, McGinn RJ, Liu CY, Kellis SS, Lee B.   +11 more
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Flexible Recurrent Neural Networks

2021
We introduce two methods enabling recurrent neural networks (RNNs) to trade off accuracy for computational cost during the analysis of a sequence. This opens up the possibility to adapt RNNs in real time to changing computational constraints, such as when running on shared hardware with other processes or in mobile edge computing nodes.
Anne Lambert, Françoise Le Bolzer, François Schnitzler   +2 more
openaire   +1 more source

Bidirectional recurrent neural networks [PDF]

IEEE Transactions on Signal Processing, 1997
In the first part of this paper, a regular recurrent neural network (RNN) is extended to a bidirectional recurrent neural network (BRNN). The BRNN can be trained without the limitation of using input information just up to a preset future frame. This is accomplished by training it simultaneously in positive and negative time direction.
K K Paliwal
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IDENTIFIABILITY OF RECURRENT NEURAL NETWORKS

Econometric Theory, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Al-Falou, A. A., Trummer, D.
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Pruning in Recurrent Neural Networks

1994
Recurrent neural networks are attracting considerable interest within the neural network domain especially because of their potential in such problems as pattern completion and temporal sequence processing (Almeida, 1987; Hertz et al., 1991). As for feed-forward networks, in virtually all problems of interest the proper number of hidden units is not ...
CASTELLANO G, FANELLI A. M, PELILLO, Marcello   +2 more
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Recurrent Neural Network for Storytelling

2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016
Storytelling is the act of passing on what you want to tell other people as so interesting and true-to-life story. As the study in text mining progresses to express words, sentences and paragraphs as vector, it is possible to classify text and generate text using vectors.
YunSeok Choi, Suah Kim, Jee-Hyong Lee 0001   +2 more
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Self-Recurrent Neural Network

Substance Use & Misuse, 1998
(1998). Self-Recurrent Neural Network. Substance Use & Misuse: Vol. 33, No. 2, pp. 495-501.
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