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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Dynamic Neural Networks: A Survey.

Yizeng Han, Gao Huang, Shiji Song

    IEEE Transactions on Pattern Analysis and Machine Intelligence
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    Summary
    This summary is machine-generated.

    Dynamic neural networks adapt structures for better accuracy and efficiency. This survey categorizes these models and discusses future research directions in deep learning.

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    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Static neural networks possess fixed computational graphs and parameters during inference.
    • Dynamic neural networks offer adaptive structures or parameters for diverse inputs.
    • These adaptations yield improvements in accuracy, computational efficiency, and adaptiveness.

    Purpose of the Study:

    • To provide a comprehensive review of the rapidly developing field of dynamic neural networks.
    • To systematically categorize and analyze key research problems and future directions.

    Main Methods:

    • Categorization of dynamic networks into three main types: sample-wise, spatial-wise, and temporal-wise.
    • Systematic review of research problems including architecture design, decision-making schemes, optimization techniques, and applications.
    • Discussion of open problems and future research avenues.

    Main Results:

    • Dynamic networks are classified based on their adaptive processing: sample-wise (per-sample), spatial-wise (per-location), and temporal-wise (per-time).
    • Key research challenges and advancements in dynamic network design, optimization, and application are highlighted.
    • The review identifies current limitations and proposes future research directions.

    Conclusions:

    • Dynamic neural networks represent a significant advancement over static models, offering enhanced performance and efficiency.
    • The survey provides a structured overview of the field, essential for researchers and practitioners.
    • Further research is needed to address open problems and unlock the full potential of dynamic networks.