Results 11 to 20 of about 75,210 (267)
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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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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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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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 processing and speech data analysis.
Enmao Diao, Jie Ding 0002, Vahid Tarokh
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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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Quasi-Recurrent Neural Networks
CoRR, 2016 Submitted to conference track at ICLR ...
BRADBURY JAMES +3 more
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Journal of Advances in Modeling Earth Systems, 2023 Systematic biases in numerical weather prediction models cause forecast deviation from reality. While model biases also affect data assimilation and degrade the analysis accuracy, observation information incorporated through data assimilation can provide
A. Amemiya, M. Shlok, T. Miyoshi
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Medical Image Interpolation Using Recurrent Type-2 Fuzzy Neural Network
Frontiers in Neuroinformatics, 2021 Image interpolation is an essential process for image processing and computer graphics in wide applications to medical imaging. For image interpolation used in medical diagnosis, the two-dimensional (2D) to three-dimensional (3D) transformation can ...
Jafar Tavoosi +5 more
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