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Gradient Flow in Recurrent Nets: The Difficulty of Learning LongTerm Dependencies
Abstract
This chapter contains sections titled: Introduction Exponential Error Decay Dilemma: Avoiding Aradient Decay Prevents Long-Term Latching Remedies Conclusion ]]>
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Cited by
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Greff, K., Srivastava, R. K., Koutnik, J., Steunebrink, B. R., & Schmidhuber, J. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2582924 · Cited by 6,955
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
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Transformer-XL: Attentive language models beyond a fixed-length context
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Metadata
- Venue
- A Field Guide to Dynamical Recurrent Networks
- Publisher
- IEEE
- Published
- 2009
- OpenAlex
- W1899504021
- Cited by
- 1,246
- References
- 0
- FWCI
- 24.30
- Type
- book chapter
- Language
- en
- Open access
- closed
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- Gradient Flow in Recurrent Nets: The Difficulty of Learning LongTerm Dependencies. (2009). A Field Guide to Dynamical Recurrent Networks. https://doi.org/10.1109/9780470544037.ch14
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