Results 31 to 40 of about 53,216 (300)
Proceedings of the 34th ACM International Conference on Supercomputing, 2020 Recurrent neural networks (RNNs) have been widely adopted in temporal sequence analysis, where realtime performance is often in demand. However, RNNs suffer from heavy computational workload as the model often comes with large weight matrices. Pruning schemes have been proposed for RNNs to eliminate the redundant (close-to-zero) weight values.
Runbin Shi +8 more
openaire +4 more sources
, 2022 Project repository for [High-Speed CMOS-Free Purely Spintronic Asynchronous Recurrent Neural Network] NeuroSpinCompute Lab., The University of Texas at ...
Xuan-Hu
core +1 more source
suvdzul/Reproduce-RNN-paper: RNN missing value
, 2022 Using GRU-D to handle missing ...
suvdzul
core +1 more source
Heartbeat Sound Signal Classification Using Deep Learning
Sensors, 2019 Presently, most deaths are caused by heart disease. To overcome this situation, heartbeat sound analysis is a convenient way to diagnose heart disease. Heartbeat sound classification is still a challenging problem in heart sound segmentation and feature ...
Ali Raza +5 more
doaj +1 more source
CoRR, 2016 Many time series are generated by a set of entities that interact with one another over time. This paper introduces a broad, flexible framework to learn from multiple inter-dependent time series generated by such entities. Our framework explicitly models the entities and their interactions through time.
Ashish Bora, Sugato Basu, Joydeep Ghosh
openaire +3 more sources
RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks
Advances in Neural Information Processing Systems 35, 2022 Published as a conference paper at NeurIPS ...
Leo Kozachkov +2 more
openaire +3 more sources
Dp-Rnn: Type Ii Diabetic Prediction Using Gkfcm And Rnn
, 2021 Diabetes is a form of metabolic disorder marked by elevated persistent blood glucose (BG), leading to several severe problems in the long term. Continuous monitoring and prediction of BG concentration are needed to help diabetic patients maintain their ...
et. al., Mrs.K.Gandhimathi,
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pohl-michel/Time-series-prediction-using-a-RNN-trained-with-RTRL: First release
, 2020 <p>Prediction of multidimensional time-series data using a recurrent neural network (RNN) trained by real-time recurrent learning (RTRL) with gradient clipping.</p ...
Pohl Michel
core +1 more source
Breast Cancer Disease Prediction With Recurrent Neural Networks (RNN) [PDF]
International Journal of Industrial Engineering and Production Research, 2020 Cancer is a consortium of diseases which comprises abnormal increase in cells growth by having potential to occupy and attack the entire body. According to study breast cancer is the most likely occurs in the women and which became the second biggest ...
sangapu venkata appaji +3 more
doaj +1 more source