Tham khảo Bộ nhớ dài-ngắn hạn

↑ Mạng neural hồi quy cheatsheet, Standford University.
↑ Sepp Hochreiter; Jürgen Schmidhuber (1997). “Long short-term memory”. Neural Computation 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735.
↑ Graves, A.; Liwicki, M.; Fernandez, S.; Bertolami, R.; Bunke, H.; Schmidhuber, J. (2009). “A Novel Connectionist System for Improved Unconstrained Handwriting Recognition” (PDF). IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (5): 855–868. PMID 19299860. doi:10.1109/tpami.2008.137. Đã bỏ qua tham số không rõ |citeseerx= (trợ giúp)
↑ Sak, Hasim; Senior, Andrew; Beaufays, Francoise (2014). “Long Short-Term Memory recurrent neural network architectures for large scale acoustic modeling” (PDF). Bản gốc (PDF) lưu trữ ngày 24 tháng 4 năm 2018. Đã bỏ qua tham số không rõ |url-status= (trợ giúp)
↑ Li, Xiangang; Wu, Xihong (ngày 15 tháng 10 năm 2014). "Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition". arΧiv: [cs.CL].
↑ Mayer, H.; Gomez, F.; Wierstra, D.; Nagy, I.; Knoll, A.; Schmidhuber, J. (tháng 10 năm 2006). A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks. 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. tr. 543–548. ISBN 978-1-4244-0258-8. doi:10.1109/IROS.2006.282190. Đã bỏ qua tham số không rõ |citeseerx= (trợ giúp)
↑ Wierstra, Daan; Schmidhuber, J.; Gomez, F. J. (2005). “Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning”. Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI), Edinburgh: 853–858.
↑ Graves, A.; Schmidhuber, J. (2005). “Framewise phoneme classification with bidirectional LSTM and other neural network architectures”. Neural Networks 18 (5–6): 602–610. PMID 16112549. doi:10.1016/j.neunet.2005.06.042. Đã bỏ qua tham số không rõ |citeseerx= (trợ giúp)
↑ Fernández, Santiago; Graves, Alex; Schmidhuber, Jürgen (2007). An Application of Recurrent Neural Networks to Discriminative Keyword Spotting. Proceedings of the 17th International Conference on Artificial Neural Networks. ICANN'07 (Berlin, Heidelberg: Springer-Verlag). tr. 220–229. ISBN 978-3540746935.
↑ Graves, Alex; Mohamed, Abdel-rahman; Hinton, Geoffrey (2013). “Speech Recognition with Deep Recurrent Neural Networks”. Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on: 6645–6649. ISBN 978-1-4799-0356-6. arXiv:1303.5778. doi:10.1109/ICASSP.2013.6638947.
↑ Gers, F.; Schraudolph, N.; Schmidhuber, J. (2002). “Learning precise timing with LSTM recurrent networks” (PDF). Journal of Machine Learning Research 3: 115–143.
↑ Eck, Douglas; Schmidhuber, Jürgen (ngày 28 tháng 8 năm 2002). Learning the Long-Term Structure of the Blues. Artificial Neural Networks — ICANN 2002. Lecture Notes in Computer Science 2415 (Springer, Berlin, Heidelberg). tr. 284–289. ISBN 978-3540460848. doi:10.1007/3-540-46084-5_47. Đã bỏ qua tham số không rõ |citeseerx= (trợ giúp)
↑ Schmidhuber, J.; Gers, F.; Eck, D.; Schmidhuber, J.; Gers, F. (2002). “Learning nonregular languages: A comparison of simple recurrent networks and LSTM”. Neural Computation 14 (9): 2039–2041. PMID 12184841. doi:10.1162/089976602320263980. Đã bỏ qua tham số không rõ |citeseerx= (trợ giúp)
↑ Gers, F. A.; Schmidhuber, J. (2001). “LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages” (PDF). IEEE Transactions on Neural Networks 12 (6): 1333–1340. PMID 18249962. doi:10.1109/72.963769.
↑ Perez-Ortiz, J. A.; Gers, F. A.; Eck, D.; Schmidhuber, J. (2003). “Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets”. Neural Networks 16 (2): 241–250. PMID 12628609. doi:10.1016/s0893-6080(02)00219-8. Đã bỏ qua tham số không rõ |citeseerx= (trợ giúp)
↑ A. Graves, J. Schmidhuber. Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks. Advances in Neural Information Processing Systems 22, NIPS'22, pp 545–552, Vancouver, MIT Press, 2009.
↑ Graves, Alex; Fernández, Santiago; Liwicki, Marcus; Bunke, Horst; Schmidhuber, Jürgen (2007). Unconstrained Online Handwriting Recognition with Recurrent Neural Networks. Proceedings of the 20th International Conference on Neural Information Processing Systems. NIPS'07 (USA: Curran Associates Inc.). tr. 577–584. ISBN 9781605603520.
↑ M. Baccouche, F. Mamalet, C Wolf, C. Garcia, A. Baskurt. Sequential Deep Learning for Human Action Recognition. 2nd International Workshop on Human Behavior Understanding (HBU), A.A. Salah, B. Lepri ed. Amsterdam, Netherlands. pp. 29–39. Lecture Notes in Computer Science 7065. Springer. 2011
↑ Huang, Jie; Zhou, Wengang; Zhang, Qilin; Li, Houqiang; Li, Weiping (ngày 30 tháng 1 năm 2018). "Video-based Sign Language Recognition without Temporal Segmentation". arΧiv:1801.10111 [cs.CV].
↑ Hochreiter, S.; Heusel, M.; Obermayer, K. (2007). “Fast model-based protein homology detection without alignment”. Bioinformatics 23 (14): 1728–1736. PMID 17488755. doi:10.1093/bioinformatics/btm247. Đã bỏ qua tham số không rõ |doi-access= (trợ giúp)
↑ Thireou, T.; Reczko, M. (2007). “Bidirectional Long Short-Term Memory Networks for predicting the subcellular localization of eukaryotic proteins”. IEEE/ACM Transactions on Computational Biology and Bioinformatics 4 (3): 441–446. PMID 17666763. doi:10.1109/tcbb.2007.1015.
↑ Malhotra, Pankaj; Vig, Lovekesh; Shroff, Gautam; Agarwal, Puneet (tháng 4 năm 2015). “Long Short Term Memory Networks for Anomaly Detection in Time Series” (PDF). European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning — ESANN 2015.
↑ Tax, N.; Verenich, I.; La Rosa, M.; Dumas, M. (2017). Predictive Business Process Monitoring with LSTM neural networks. Proceedings of the International Conference on Advanced Information Systems Engineering (CAiSE). Lecture Notes in Computer Science. 10253. tr. 477–492. ISBN 978-3-319-59535-1. arXiv:1612.02130. doi:10.1007/978-3-319-59536-8_30.
↑ Choi, E.; Bahadori, M.T.; Schuetz, E.; Stewart, W.; Sun, J. (2016). “Doctor AI: Predicting Clinical Events via Recurrent Neural Networks”. Proceedings of the 1st Machine Learning for Healthcare Conference 56: 301–318. Bibcode:2015arXiv151105942C. PMC 5341604. PMID 28286600. arXiv:1511.05942.
↑ Jia, Robin; Liang, Percy (2016-06-11). Arxiv:1606.03622. arXiv:1606.03622 [cs].
↑ Wang, Le; Duan, Xuhuan; Zhang, Qilin; Niu, Zhenxing; Hua, Gang; Zheng, Nanning (ngày 22 tháng 5 năm 2018). “Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation” (PDF). Sensors 18 (5): 1657. ISSN 1424-8220. PMC 5982167. PMID 29789447. doi:10.3390/s18051657.
↑ Duan, Xuhuan; Wang, Le; Zhai, Changbo; Zheng, Nanning; Zhang, Qilin; Niu, Zhenxing; Hua, Gang (2018). Joint Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation. 25th IEEE International Conference on Image Processing (ICIP). ISBN 978-1-4799-7061-2. doi:10.1109/icip.2018.8451692.
↑ Orsini, F.; Gastaldi, M.; Mantecchini, L.; Rossi, R. (2019). Neural networks trained with WiFi traces to predict airport passenger behavior. 6th International Conference on Models and Technologies for Intelligent Transportation Systems. Krakow: IEEE. arXiv:1910.14026. doi:10.1109/MTITS.2019.8883365. 8883365.
↑ Zhao, Z.; Chen, W.; Wu, X.; Chen, P.C.Y.; Liu, J. (2017). “LSTM network: A deep learning approach for Short-term traffic forecast”. IET Intelligent Transport Systems 11 (2): 68–75. doi:10.1049/iet-its.2016.0208.
↑ Gupta A, Müller AT, Huisman BJH, Fuchs JA, Schneider P, Schneider G (2018). “Generative Recurrent Networks for De Novo Drug Design.”. Mol Inform 37 (1-2). PMC 5836943. PMID 29095571. doi:10.1002/minf.201700111.