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Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network

Physica. D, 2020-03, Vol.404, p.132306, Article 132306

Sherstinsky, Alex

2020

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Time series forecasting of COVID-19 transmission in Canada using LSTM networks

Chaos, solitons and fractals, 2020-06, Vol.135, p.109864-109864, Article 109864

2020

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LSTM: A Search Space Odyssey

IEEE transaction on neural networks and learning systems, 2017-10, Vol.28 (10), p.2222-2232

2017

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Classification of Skin Disease Using Deep Learning Neural Networks with MobileNet V2 and LSTM

Sensors (Basel, Switzerland), 2021-04, Vol.21 (8), p.2852

2021

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Short-term runoff prediction with GRU and LSTM networks without requiring time step optimization during sample generation

Journal of hydrology (Amsterdam), 2020-10, Vol.589, p.125188, Article 125188

2020

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Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM

Chaos, solitons and fractals, 2020-11, Vol.140, p.110212-110212, Article 110212

2020

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Deep Learning With Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development

IEEE transactions on industrial electronics (1982), 2021-05, Vol.68 (5), p.4404-4414

2021

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A day-ahead PV power forecasting method based on LSTM-RNN model and time correlation modification under partial daily pattern prediction framework

Energy conversion and management, 2020-05, Vol.212, p.112766, Article 112766

2020

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A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures

Neural computation, 2019-07, Vol.31 (7), p.1235-1270

2019

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Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM

Energy (Oxford), 2021-07, Vol.227, p.120492, Article 120492

2021

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A Hybrid Deep Learning Model With Attention-Based Conv-LSTM Networks for Short-Term Traffic Flow Prediction

IEEE transactions on intelligent transportation systems, 2021-11, Vol.22 (11), p.6910-6920

2021

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Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas

Journal of hydrology (Amsterdam), 2018-06, Vol.561, p.918-929

2018

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Physics-informed multi-LSTM networks for metamodeling of nonlinear structures

Computer methods in applied mechanics and engineering, 2020-09, Vol.369, p.113226, Article 113226

2020

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Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

IEEE transactions on image processing, 2019-07, Vol.28 (7), p.3286-3300

2019

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A bidirectional LSTM deep learning approach for intrusion detection

Expert systems with applications, 2021-12, Vol.185, p.115524, Article 115524

2021

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Multi-hour and multi-site air quality index forecasting in Beijing using CNN, LSTM, CNN-LSTM, and spatiotemporal clustering

Expert systems with applications, 2021-05, Vol.169, p.114513, Article 114513

2021

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A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning

Water resources research, 2020-01, Vol.56 (1), p.n/a

2020

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Predicting residential energy consumption using CNN-LSTM neural networks

Energy (Oxford), 2019-09, Vol.182, p.72-81

2019

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Weakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos

IEEE transactions on pattern analysis and machine intelligence, 2020-09, Vol.42 (9), p.2306-2320

2020

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Carbon price forecasting based on CEEMDAN and LSTM

Applied energy, 2022-04, Vol.311, p.118601, Article 118601

2022

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Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network

IEEE transactions on smart grid, 2019-01, Vol.10 (1), p.841-851

2019

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Photovoltaic power forecasting based LSTM-Convolutional Network

Energy (Oxford), 2019-12, Vol.189, p.116225, Article 116225

2019

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Financial time series forecasting model based on CEEMDAN and LSTM

Physica A, 2019-04, Vol.519, p.127-139

2019

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A Data-Driven Auto-CNN-LSTM Prediction Model for Lithium-Ion Battery Remaining Useful Life

IEEE transactions on industrial informatics, 2021-05, Vol.17 (5), p.3478-3487

2021

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Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models

Expert systems with applications, 2018-08, Vol.103, p.25-37

2018

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Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network

Time series forecasting of COVID-19 transmission in Canada using LSTM networks

LSTM: A Search Space Odyssey

Classification of Skin Disease Using Deep Learning Neural Networks with MobileNet V2 and LSTM

Short-term runoff prediction with GRU and LSTM networks without requiring time step optimization during sample generation

Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM

Deep Learning With Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development

A day-ahead PV power forecasting method based on LSTM-RNN model and time correlation modification under partial daily pattern prediction framework

A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures

Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM

A Hybrid Deep Learning Model With Attention-Based Conv-LSTM Networks for Short-Term Traffic Flow Prediction

Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas

Physics-informed multi-LSTM networks for metamodeling of nonlinear structures

Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

A bidirectional LSTM deep learning approach for intrusion detection

Multi-hour and multi-site air quality index forecasting in Beijing using CNN, LSTM, CNN-LSTM, and spatiotemporal clustering

A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning

Predicting residential energy consumption using CNN-LSTM neural networks

Weakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos

Carbon price forecasting based on CEEMDAN and LSTM

Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network

Photovoltaic power forecasting based LSTM-Convolutional Network

Financial time series forecasting model based on CEEMDAN and LSTM

A Data-Driven Auto-CNN-LSTM Prediction Model for Lithium-Ion Battery Remaining Useful Life

Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models

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