The DOI matches its Crossref record; 155 of the 155 references it cites were found in a registry or an index.
Recurrent Neural Networks: A Comprehensive Review of Architectures, Variants, and Applications
Open accessAbstract
Recurrent neural networks (RNNs) have significantly advanced the field of machine learning (ML) by enabling the effective processing of sequential data. This paper provides a comprehensive review of RNNs and their applications, highlighting advancements in architectures, such as long short-term memory (LSTM) networks, gated recurrent units (GRUs), bidirectional LSTM (BiLSTM), echo state networks (ESNs), peephole LSTM, and stacked LSTM. The study examines the application of RNNs to different domains, including natural language processing (NLP), speech recognition, time series forecasting, autonomous vehicles, and anomaly detection. Additionally, the study discusses recent innovations, such as the integration of attention mechanisms and the development of hybrid models that combine RNNs with convolutional neural networks (CNNs) and transformer architectures. This review aims to provide ML researchers and practitioners with a comprehensive overview of the current state and future directions of RNN research.
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Cites
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Gradient-based learning applied to document recognition
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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
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Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014) · arXiv · doi:10.48550/arxiv.1412.3555 · Cited by 11,008
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Effective Approaches to Attention-based Neural Machine Translation
Luong, T., Pham, H., & Manning, C. D. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d15-1166 · Cited by 8,382
Building a Large Annotated Corpus of English: The Penn Treebank
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A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
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Cited by
Fahim, Y. A., Hasani, I. W., Kabba, S., & Ragab, W. M. (2025) · European Journal of Medical Research · doi:10.1186/s40001-025-03196-w · Cited by 329
Mienye, I. D., Obaido, G., Jere, N., Mienye, E., Aruleba, K., Emmanuel, I. D., & Ogbuokiri, B. (2024) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2024.101587 · Cited by 212
Self-citationDini, P., & Paolini, D. (2025) · Batteries · doi:10.3390/batteries11030107 · Cited by 40
A Hybrid Modeling Framework for Predictive Digital Twins of CHO Cell Culture
Richelle, A., Andersson, D., Antonakoudis, A., Jakobsson, J., Pijeaud, S., Vernersson, A., & Trygg, J. (2025) · doi:10.1101/2025.11.24.690194 · Cited by 6
Metadata
- Authors
- Mienye, I. D., Swart, T. G., & Obaido, G.
- Venue
- Information
- Publisher
- MDPI AG
- Published
- 2024-08-25
- Volume
- 15
- Issue
- 9
- Pages
- 517
- ISSN
- 2078-2489 (ISSN-L)
- OpenAlex
- W4401889742
- Cited by
- 732
- References
- 155
- FWCI
- 108.94
- Type
- journal article
- Language
- en
- Open access
- gold
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