Results 11 to 20 of about 296,489 (278)
Restricted Recurrent Neural Networks [PDF]
2019 IEEE International Conference on Big Data (Big Data), 2019 Recurrent Neural Network (RNN) and its variations such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), have become standard building blocks for learning online data of sequential nature in many research areas, including natural language ...
Diao, Enmao, Ding, Jie, Tarokh, Vahid
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Discontinuities in recurrent neural networks [PDF]
Neural Computation, 1997 This paper studies the computational power of various discontinuous real computational models that are based on the classical analog recurrent neural network (ARNN).
Gavaldà Mestre, Ricard +1 more
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Recurrent Neural Network Grammars [PDF]
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 We introduce recurrent neural network grammars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing and language modeling. Experiments show that they provide better parsing in English than any single previously published supervised generative model and better
Dyer, Chris +3 more
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Shuffling Recurrent Neural Networks
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 We propose a novel recurrent neural network model, where the hidden state hₜ is obtained by permuting the vector elements of the previous hidden state hₜ₋₁ and adding the output of a learned function β(xₜ) of the input xₜ at time t. In our model, the prediction is given by a second learned function, which is applied to the hidden state s(hₜ).
Michael Rotman, Lior Wolf
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Reinforcement Learning for Central Pattern Generation in Dynamical Recurrent Neural Networks
Frontiers in Computational Neuroscience, 2022 Lifetime learning, or the change (or acquisition) of behaviors during a lifetime, based on experience, is a hallmark of living organisms. Multiple mechanisms may be involved, but biological neural circuits have repeatedly demonstrated a vital role in the
Jason A. Yoder +3 more
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Stability and Synchronization of Switched Multi-Rate Recurrent Neural Networks
IEEE Access, 2021 Several designs of recurrent neural networks have been proposed in the literature involving different clock times. However, the stability and synchronization of this kind of system have not been studied.
Victoria Ruiz +3 more
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Deductron—A Recurrent Neural Network [PDF]
Frontiers in Applied Mathematics and Statistics, 2020 34 pages, contains Python code, Python code requires data file data.py (should be included in the archive)
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A Deep Multi-Task Learning Approach for Bioelectrical Signal Analysis
Mathematics, 2023 Deep learning is a promising technique for bioelectrical signal analysis, as it can automatically discover hidden features from raw data without substantial domain knowledge.
Jishu K. Medhi +3 more
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Deep Sparse Learning for Automatic Modulation Classification Using Recurrent Neural Networks
Sensors, 2021 Deep learning models, especially recurrent neural networks (RNNs), have been successfully applied to automatic modulation classification (AMC) problems recently.
Ke Zang, Wenqi Wu, Wei Luo
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