Spoken Language Identification System Using Convolutional Recurrent Neural Network by Adal A. Alashban, Mustafa A. Qamhan, Ali H. Meftah, Yousef A. Alotaibi

“…The proposed system uses a hybrid Convolutional Recurrent Neural Network (CRNN), which combines a Convolutional Neural Network (CNN) with a Recurrent Neural Network (RNN) network, for spoken language identification on seven languages, including Arabic, chosen from subsets of the Mozilla Common Voice (MCV) corpus. …”
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On Optimization Techniques for the Construction of an Exponential Estimate for Delayed Recurrent Neural Networks by Vasyl Martsenyuk, Stanislaw Rajba, Mikolaj Karpinski

Subjects: “…recurrent neural network…”
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A Dilated Recurrent Neural Network-Based Model for Graph Embedding by Xiao Han, Chunhong Zhang, Yang Ji, Zheng Hu

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Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification by Kaisheng Liao, Yaodong Zhao, Jie Gu, Yaping Zhang, Yi Zhong

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Application of ensemble of recurrent neural networks for forecasting of stock market sentiments by Nijole Maknickiene, Indre Lapinskaite, Algirdas Maknickas

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Applying Recurrent Neural Networks for Anomaly Detection in Electrocardiogram Sensor Data by Ana Minic, Luka Jovanovic, Nebojsa Bacanin, Catalin Stoean, Miodrag Zivkovic, Petar Spalevic, Aleksandar Petrovic, Milos Dobrojevic, Ruxandra Stoean

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Comparison of Feedforward and Recurrent Neural Network in Forecasting Chaotic Dynamical System by Avadis Hacınlıyan, Engin Kandıran

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Discovery of novel chemical reactions by deep generative recurrent neural network by William Bort, Igor I. Baskin, Timur Gimadiev, Artem Mukanov, Ramil Nugmanov, Pavel Sidorov, Gilles Marcou, Dragos Horvath, Olga Klimchuk, Timur Madzhidov, Alexandre Varnek

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Chemlistem: chemical named entity recognition using recurrent neural networks by Peter Corbett, John Boyle

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Recurrent Neural Network and Reinforcement Learning Model for COVID-19 Prediction by R. Lakshmana Kumar, Firoz Khan, Sadia Din, Shahab S. Band, Amir Mosavi, Amir Mosavi, Ebuka Ibeke

“…This article constructs a model using Recurrent Neural Networks (RNN), particularly the Modified Long Short-Term Memory (MLSTM) model, to forecast the count of newly affected individuals, losses, and cures in the following few days. …”
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Epigenome-based splicing prediction using a recurrent neural network. by Donghoon Lee, Jing Zhang, Jason Liu, Mark Gerstein

“…Given this, we tried to build an interpretable model that mimics the physical layout of splicing regulation where the chromatin context progressively changes as the Pol II moves along the guide DNA. We used a recurrent-neural-network architecture to predict the inclusion of a spliced exon based on adjacent epigenetic signals, and we showed that distinct spatio-temporal features of these signals were key determinants of model outcome, in addition to the actual nucleotide sequence of the guide DNA strand. …”
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Extracting the dynamics of the Hodgkin-Huxley model using recurrent neural networks by Andoni Sari, Saggar Manish, Meriçli Tekin, Miikkulainen Risto

Dynamic Preservation for a Class of Semi-Discrete Recurrent Neural Networks by Songfang Jia, Yanheng Chen

“…The dynamic preservation in discrete simulations of the recurrent neural networks (RNNs) with discrete and infinite distributive asynchronous time delays is addressed. …”
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Relation Classification via Recurrent Neural Network with Attention and Tensor Layers by Runyan Zhang, Fanrong Meng, Yong Zhou, Bing Liu

Subjects: “…bidirectional recurrent neural network (rnns)…”
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Rental Prediction in Bicycle-Sharing System Using Recurrent Neural Network by Eric Hsueh-Chan Lu, Zhan-Qing Lin

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Engineering recurrent neural networks from task-relevant manifolds and dynamics. by Eli Pollock, Mehrdad Jazayeri

“…Many cognitive processes involve transformations of distributed representations in neural populations, creating a need for population-level models. Recurrent neural network models fulfill this need, but there are many open questions about how their connectivity gives rise to dynamics that solve a task. …”
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VBF Event Classification with Recurrent Neural Networks at ATLAS’s LHC Experiment by Silvia Auricchio, Francesco Cirotto, Antonio Giannini

“…A novel machine learning (ML) approach based on a recurrent neural network (RNN) for event topology identification in high energy physics (HEP) is presented. …”
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Software Reliability Prediction through Encoder-Decoder Recurrent Neural Networks by Chen Li, Junjun Zheng, Hiroyuki Okamura, Tadashi Dohi

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Visual analytics tool for the interpretation of hidden states in recurrent neural networks by Rafael Garcia, Tanja Munz, Daniel Weiskopf

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From tensor-network quantum states to tensorial recurrent neural networks by Dian Wu, Riccardo Rossi, Filippo Vicentini, Giuseppe Carleo

“…We show that any matrix product state (MPS) can be exactly represented by a recurrent neural network (RNN) with a linear memory update. …”
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