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Updated: Jun 6, 2025

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions
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通过使用集成梯度来解释高斯过程模型

Fan Zhang1, Naoaki Ono1,2, Shigehiko Kanaya1,2

  • 1Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara, 630-0192, Japan.

Molecular informatics
|November 26, 2024
PubMed
概括

本研究引入了一种新的方法,通过使用集成梯度 (IG) 来解释高斯过程回归 (GPR) 预测. 该方法通过详细说明特征贡献来解释预测不确定性,增强模型的信任和理解.

关键词:
可以解释的人工智能AI这是高斯斯过程.集成梯度的综合梯度.

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