LSTM: A Search Space Odyssey

Greff, Klaus, Srivastava, Rupesh K., Koutnik, Jan, Steunebrink, Bas R., Schmidhuber, Jurgen·2017·IEEE Transactions on Neural Networks and Learning Systems

Cited by (1,013)

Items 101–200 of 1,013

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    Romero F.A.B. de Morais, Vuong Le, Truyen Tran, Budhaditya Saha, Moussa Reda Mansour, Svetha Venkatesh · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
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    Sagheer, Alaa, Kotb, Mostafa · 2019 · Scientific Reports
  5. Monthly runoff forecasting based on LSTM–ALO model
    Xiaohui Yuan, Chen Chen, Xiaohui Lei, Yanbin Yuan, Rana Muhammad Adnan · 2018 · Stochastic Environmental Research and Risk Assessment
  6. Sequential Fault Diagnosis Based on LSTM Neural Network
    Haitao Zhao, Shaoyuan Sun, Bo Jin · 2018 · IEEE Access
  7. Time Series Prediction Based on LSTM-Attention-LSTM Model
    Xianyun Wen, Weibang Li · 2023 · IEEE Access
  8. A deep learning approach for detecting traffic accidents from social media data
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  10. Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons
    Zhihong Pang, Fuxin Niu, Zheng D. O’Neill · 2020 · Renewable Energy
  11. Web traffic anomaly detection using C-LSTM neural networks
    Tae Young Kim, Sung‐Bae Cho · 2018 · Expert Systems with Applications
  12. Improving streamflow prediction in the WRF-Hydro model with LSTM networks
    Kyeungwoo Cho, Yeonjoo Kim · 2021 · Journal of Hydrology
  13. From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?
    Wei Zhi, Dapeng Feng, Wen‐Ping Tsai, Gary Sterle, Adrian Adam Harpold, Chaopeng Shen, Li Li · 2021 · Environmental Science & Technology
  14. A nonlinear hybrid wind speed forecasting model using LSTM network, hysteretic ELM and Differential Evolution algorithm
    Ya-Lan Hu, Liang Chen · 2018 · Energy Conversion and Management
  15. A Comprehensive Analysis of Deep Regression
    Stéphane Lathuilière, Pablo Mesejo, Xavier Alameda-Pineda, Radu Horaud · 2020 · IEEE Transactions on Pattern Analysis and Machine Intelligence
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    Shengxian Wan, Yanyan Lan, Jiafeng Guo, Jun Xu, Liang Pang, Xueqi Cheng · 2016 · Proceedings of the AAAI Conference on Artificial Intelligence
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    John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu · 2015 · arXiv (Cornell University)
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    Ruixing Huang, Chengxue Ma, Jun Ma, Xiaoliu Huangfu, Qiang He · 2021 · Water Research
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    Weijiang Li, Fang Qi, Ming Tang, Zhengtao Yu · 2020 · Neurocomputing
  20. FP-DNN: An Automated Framework for Mapping Deep Neural Networks onto FPGAs with RTL-HLS Hybrid Templates
    Yijin Guan, Hao Liang, Ningyi Xu, Wenqiang Wang, Shaoshuai Shi, Xi Chen, Guangyu Sun, Wei Zhang, Jason Cong · 2017 · IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM)
  21. Fake News identification on Twitter with Hybrid CNN and RNN Models
    Oluwaseun Ajao, Deepayan Bhowmik, Shahrzad A. Zargari · 2018 · e-space (Manchester Metropolitan University)
  22. From Regional to Global Brain: A Novel Hierarchical Spatial-Temporal Neural Network Model for EEG Emotion Recognition
    Yang Li, Wenming Zheng, Lei Wang, Yuan Zong, Zhen Cui · 2019 · IEEE Transactions on Affective Computing
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    Chen, Kaixuan, Zhang, Dalin, Yao, Lina, Guo, Bin, Yu, Zhiwen, Liu, Yunhao · 2020 · arXiv
  24. Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals
    Yuxin Zhang, Yiqiang Chen, Jindong Wang, Zhiwen Pan · 2021 · IEEE Transactions on Knowledge and Data Engineering
  25. Predicting COVID-19 in China Using Hybrid AI Model
    Nanning Zheng, Shaoyi Du, Jianji Wang, He Zhang, Wenting Cui, Zijian Kang, Tao Yang, Bin Lou, Yuting Chi, Hong Long et al. · 2020 · IEEE Transactions on Cybernetics
  26. Predicting stock market index using LSTM
    Hum Nath Bhandari, Binod Rimal, Nawa Raj Pokhrel, Ramchandra Rimal, Keshab Raj Dahal, Rajendra K C Khatri · 2022 · Machine Learning with Applications
  27. Deep learning detecting fraud in credit card transactions
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  29. Simple Recurrent Units for Highly Parallelizable Recurrence
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  30. A Survey of Modulation Classification Using Deep Learning: Signal Representation and Data Preprocessing
    Shengliang Peng, Shujun Sun, Yudong Yao · 2021 · IEEE Transactions on Neural Networks and Learning Systems
  31. An improved similarity-based prognostic algorithm for RUL estimation using an RNN autoencoder scheme
    Wennian Yu, Il Yong Kim, Chris Mechefske · 2020 · Reliability Engineering & System Safety
  32. Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review
    Sibo Lucas Cheng, César Quilodrán-Casas, Said Ouala, Alban Farchi, Che Liu, Pierre Tandeo, Ronan Fablet, Didier Lucor, Bertrand Iooss, Julien Brajard et al. · 2023 · IEEE/CAA Journal of Automatica Sinica
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    Alberto Gasparin, Slobodan Luković, Cesare Alippi · 2021 · CAAI Transactions on Intelligence Technology
  34. Electricity Price Forecasting Using Recurrent Neural Networks
    Umut Uğurlu, İlkay Öksüz, Oktay Taş · 2018 · Energies
  35. A CNN-BiLSTM Model for Document-Level Sentiment Analysis
    Maryem Rhanoui, Mounia Mikram, Siham Yousfi, Soukaina Barzali · 2019 · Machine Learning and Knowledge Extraction
  36. Wind speed prediction method using Shared Weight Long Short-Term Memory Network and Gaussian Process Regression
    Zhendong Zhang, Lei Ye, Hui Qin, Yongqi Liu, Chao Wang, Xiang Jun Yu, Xingli Yin, Jie Li · 2019 · Applied Energy
  37. A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms
    Mohammad J. Hamayel, Amani Yousef Owda · 2021 · AI
  38. Character-Based LSTM-CRF with Radical-Level Features for Chinese Named Entity Recognition
    Chuanhai Dong, Jiajun Zhang, Chengqing Zong, Masanori Hattori, Hui Di · 2016 · Lecture notes in computer science
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    Federico Landi, Lorenzo Baraldi, Marcella Cornia, Rita Cucchiara · 2021 · Neural Networks
  40. Mixed Neural Network Approach for Temporal Sleep Stage Classification
    Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul McMahan Matthews, Yike Guo · 2017 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  41. Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models
    Babak Abbaschian, Daniel Sierra-Sosa, Adel Said Elmaghraby · 2021 · Sensors
  42. Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection
    Kanjo, Eiman, Younis, Eman M.G., Ang, Chee Siang · 2019 · Information Fusion
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    DiPietro, Robert, Hager, Gregory D. · 2020 · Handbook of Medical Image Computing and Computer Assisted Intervention
  44. Rainfall prediction: A comparative analysis of modern machine learning algorithms for time-series forecasting
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  45. Deep Evidential Regression
    Alexander Amini, Wilko Schwarting, Ava P. Soleimany, Daniela L. Rus · 2019 · arXiv (Cornell University)
  46. Improved Transition-based Parsing by Modeling Characters instead of Words with LSTMs
    Miguel Ballesteros, Chris Dyer, Noah A. Smith · 2015 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
  47. Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts
    Yanlai Zhou, Fi‐John Chang, Li‐Chiu Chang, I-Feng Kao, Yi-Shin Wang · 2018 · Journal of Cleaner Production
  48. Land Cover Classification via Multitemporal Spatial Data by Deep Recurrent Neural Networks
    Dino Ienco, Raffaele Gaetano, Claire Dupaquier, Pierre Maurel · 2017 · IEEE Geoscience and Remote Sensing Letters
  49. Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation
    Pengpeng Zhao, Haifeng Zhu, Yanchi Liu, Jiajie Xu, Zhixu Li, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou · 2019 · Proceedings of the AAAI Conference on Artificial Intelligence
  50. Speech Emotion Classification Using Attention-Based LSTM
    Yue Xie, Ruiyu Liang, Zhenlin Liang, Chengwei Huang, Cairong Zou, Björn Wolfgang Schuller · 2019 · IEEE/ACM Transactions on Audio Speech and Language Processing
  51. Recurrent Neural Networks for Short-Term Load Forecasting
    Filippo Maria Bianchi, Enrico Maiorino, Michael Kampffmeyer, Antonello Rizzi, Robert Jenssen · 2017 · SpringerBriefs in computer science
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    Serban, Iulian Vlad, García-Durán, Alberto, Gulcehre, Caglar, Ahn, Sungjin, Chandar, Sarath, Courville, Aaron, Bengio, Yoshua · 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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  56. An Analysis of Encoder Representations in Transformer-Based Machine Translation
    Raganato, Alessandro, Tiedemann, Jörg · 2018 · Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP
  57. Improving air quality prediction accuracy at larger temporal resolutions using deep learning and transfer learning techniques
    Jun Ma, Jack C.P. Cheng, Changqing Lin, Yi Tan, Jingcheng Zhang · 2019 · Atmospheric Environment
  58. Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
    David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson · 2021 · Sensors
  59. Grid Long Short-Term Memory
    Nal Kalchbrenner, Ivo Danihelka, Alex Graves · 2015 · arXiv (Cornell University)
  60. Fake News Detection using Bi-directional LSTM-Recurrent Neural Network
    Pritika Bahad, Preeti Saxena, Raj Kamal · 2019 · Procedia Computer Science
  61. diffGrad: An Optimization Method for Convolutional Neural Networks
    Shiv Ram Dubey, Soumendu Chakraborty, Swalpa Kumar Roy, Snehasis Mukherjee, Satish Kumar Singh, B.B. Chaudhuri · 2019 · IEEE Transactions on Neural Networks and Learning Systems
  62. A Novel Hybrid Short-Term Load Forecasting Method of Smart Grid Using MLR and LSTM Neural Network
    Jian Li, Daiyu Deng, Junbo Zhao, Dongsheng Cai, Weihao Hu, Man Zhang, Qi ping Huang · 2020 · IEEE Transactions on Industrial Informatics
  63. Machine learning for hydrologic sciences: An introductory overview
    Tianfang Xu, Feng Liang · 2021 · Wiley Interdisciplinary Reviews Water
  64. Improving One-Stage Visual Grounding by Recursive Sub-query Construction
    Zhengyuan Yang, Tianlang Chen, Liwei Wang, Jiebo Luo · 2020 · Lecture notes in computer science
  65. AttnSense: Multi-level Attention Mechanism For Multimodal Human Activity Recognition
    Ma, HaoJie, Li, Wenzhong, Zhang, Xiao, Gao, Songcheng, Lu, Sanglu · 2019 · Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
  66. Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals
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  68. Deep learning and transfer learning models of energy consumption forecasting for a building with poor information data
    Yuan Gao, Yingjun Ruan, Chengkuan Fang, Shuai Yin · 2020 · Energy and Buildings
  69. Personalized Vehicle Trajectory Prediction Based on Joint Time-Series Modeling for Connected Vehicles
    Yang Xing, Chen Lv, Dongpu Cao · 2019 · IEEE Transactions on Vehicular Technology
  70. Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network
    Gong Cheng, Xinzhi Wang, Yurong He · 2021 · Energy
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    Xiuling Huang, Jie Sun, Jian Sun · 2018 · Transportation Research Part C Emerging Technologies
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    Amiya Kumar Sahu, Suraj Kumar Sharma, M. Tanveer, Rohit Raja · 2021 · Computer Communications
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    Ahmed Elsheikh, Soumaya Yacout, Mohamed-Salah Ouali · 2018 · Neurocomputing
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    Mahbubul Alam, Manar D. Samad, Lasitha Vidyaratne, Alexander Glandon, Khan M. Iftekharuddin · 2020 · Neurocomputing
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    Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal · 2020 · medRxiv
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    Jiaqing Kou, Weiwei Zhang · 2021 · Progress in Aerospace Sciences
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