Sensitivity – Local index to control chaoticity or gradient globally

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Sensitivity – Local index to control chaoticity or gradient globally –

Published:2021-11 Issue: Volume:143 Page:436-451
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Shibata Katsunari^ORCID,Ejima Takuya^ORCID,Tokumaru Yuki^ORCID,Matsuki Toshitaka^ORCID

Funder

Kayamori Foundation of Informational Science Advancement

Japan Society for the Promotion of Science

Kayamori Foundation of Informational Science

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference38 articles.

1. Layer normalization;Ba,2016

2. Learning long-term dependencies with gradient descent is difficult;Bengio;IEEE Transactions on Neural Networks,1994

3. Information processing in echo state networks at the edge of chaos;Boedecker;Theory in Biosciences,2012

4. Empirical evaluation of gated recurrent neural networks on sequence modeling;Chung,2014

5. Deep learning for time series classification: A review;Fawaz,2018

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1. The Multiple Frequency Conversion Sinusoidal Chaotic Neural Network and Its Application;Fractal and Fractional;2023-09-21

2. Computational Models That Use a Quantitative Structure–Activity Relationship Approach Based on Deep Learning;Processes;2023-04-21

3. A Deep Reinforcement Learning Approach to Edge-based IDS Packets Sampling;2022 5th International Conference on Data Science and Information Technology (DSIT);2022-07-22

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