Synaptic plasticity-based regularizer for artificial neural networks

Synaptic plasticity-based regularizer for artificial neural networks

Abstract Regularization is an important tool for the generalization of ANN models. Due to the lack of constraints, it cannot guarantee that the model will work in a real environment with input data distribution changes. Inspired by neuroplasticity, this paper introduces a bounded regularization meth...

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Bibliographic Details
Main Authors: Qais Yousef, Pu Li
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Distribution change
Model regularization
Synaptic plasticity
Variable environment
Online Access:https://doi.org/10.1038/s41598-025-91635-3
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https://doi.org/10.1038/s41598-025-91635-3

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