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Deductron—A Recurrent Neural Network [PDF]
Frontiers in Applied Mathematics and Statistics, 2020 The current paper is a study in Recurrent Neural Networks (RNN), motivated by the lack of examples simple enough so that they can be thoroughly understood theoretically, but complex enough to be realistic.
Marek Rychlik
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Recurrent neural network wave functions [PDF]
Physical Review Research, 2020 A core technology that has emerged from the artificial intelligence revolution is the recurrent neural network (RNN). Its unique sequence-based architecture provides a tractable likelihood estimate with stable training paradigms, a combination that has ...
Mohamed Hibat-Allah +4 more
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Recurrent neural network optimization for wind turbine condition prognosis
Diagnostyka, 2022 This research focuses on employing Recurrent Neural Networks (RNN) to prognosis a wind turbine operation’s health from collected vibration time series data, by using several memory cell variations, including Long Short Time Memory (LSTM), Bilateral LSTM (
Kerboua Adlen, Kelaiaia Ridha
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Recurrent Neural Network Grammars [PDF]
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 We introduce recurrent neural network grammars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing and language modeling.
Chris Dyer +3 more
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Comparison of Novel Recurrent Neural Network Over Artificial Neural network in Predicting Email spammers with improved accuracy [PDF]
E3S Web of Conferences, 2023 The main aim is to compare Novel Recurrent Neural Network over Artificial Neural Network in predicting Email spammers with improved accuracy. Material and Methods : This research study contains two groups namely Novel Recurrent Neural Network and ...
Neeharika Chillakuru, Kalaiarasi S.
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Survey on Evolutionary Recurrent Neural Networks [PDF]
Jisuanji kexue, 2023 Evolutionary computation utilizes natural selection mechanisms and genetic laws in the process of biological evolution to solve optimization problems.The accuracy and efficiency of the evolutionary recurrent neural network model depends on the ...
HU Zhongyuan, XUE Yu, ZHA Jiajie
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Research on recurrent neural network model based on weight activity evaluation [PDF]
ITM Web of Conferences, 2022 Given the complex structure and parameter redundancy of recurrent neural networks such as LSTM, related research and analysis on the structure of recurrent neural networks have been done.
Zhang Cheng +5 more
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PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 The predictive learning of spatiotemporal sequences aims to generate future images by learning from the historical context, where the visual dynamics are believed to have modular structures that can be learned with compositional subsystems.
Yun-Bo Wang +6 more
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Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network [PDF]
Physica A: Statistical Mechanics and its Applications, 2018 Because of their effectiveness in broad practical applications, LSTM networks have received a wealth of coverage in scientific journals, technical blogs, and implementation guides.
A. Sherstinsky
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Electrical engineering & Electromechanics, 2022 Purpose. This article proposes a new control strategy for static synchronous compensator in utility grid system. The proposed photovoltaic fed static synchronous compensator is utilized along with recurrent neural network based reference voltage ...
T. Praveen Kumar +2 more
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