Results 261 to 270 of about 312,321 (283)

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

PLoS One
Wang S, Xu O.
europepmc   +1 more source

Corrigendum: Gradient-free training of recurrent neural networks using random perturbations. [PDF]

Front Neurosci
Fernández JG, Keemink S, van Gerven M.
europepmc   +1 more source

Temporal Anomaly Detection in Attention-Deficit/Hyperactivity Disorder Using Recurrent Neural Networks. [PDF]

Cureus
Bouchouras G, Sofianidis G, Kotis K.
europepmc   +1 more source

Rapid context inference in a thalamocortical model using recurrent neural networks. [PDF]

Nat Commun
Zheng WL, Wu Z, Hummos A, Yang GR, Halassa MM.   +4 more
europepmc   +1 more source

Mountain Flood Level Forecasting in Small Watersheds Based on Recurrent Neural Networks and Multi-Dimensional Data

Songsong Wang, Ouguan Xu
openalex   +1 more source

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Recurrent Neural Network

2021
Recurrent neural networks (RNN) are very powerful types of neural networks and are the most promising algorithm because they are the only ones with an internal memory (Boca Raton Mhaskar et al. Learning functions: when is deep better than shallow. arXiv:1603.00988, 2016).
G. R. Kanagachidambaresan, Adarsha Ruwali, Debrup Banerjee, Kolla Bhanu Prakash   +3 more
openaire   +2 more sources

Recurrent Neural Networks

2018
We applied the generic neural network framework from Chap. 3 to specific network structures in the previous chapter. Multilayer Perceptrons and Convolutional Neural Networks fit squarely into that framework, and we were also able to modify it to capture Deep Auto-Encoders.
Anthony L. Caterini, Dong Eui Chang
  +5 more sources

Recurrent Neural Network Architectures

2017
In this chapter, we present three different recurrent neural network architectures that we employ for the prediction of real-valued time series. All the models reviewed in this chapter can be trained through the previously discussed backpropagation through time procedure.
Bianchi, Filippo Maria, Maiorino, Enrico, Kampffmeyer, Michael C., Rizzi, Antonello, Jenssen, Robert   +4 more
openaire   +2 more sources

Self-Recurrent Neural Network

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

Recurrent Neural Networks

2023
Yinhai Wang, Zhiyong Cui, Ruimin Ke
  +6 more sources