Engineering
残差高斯过程
Residual Gaussian ProcessA machine learning method that uses Gaussian Processes (GPs) to model the residual errors of a base model, improving prediction accuracy and uncertainty quantification. / 一种机器学习方法，利用高斯过程（GP）对基础模型的残差误差进行建模，以提高预测精度和不确定性量化。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-07 21:05:20
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Main parameters and performance indicators
kernel: Specifies the covariance function defining the smoothness and behavior of the function.stacking: A meta-learning technique used to combine predictions from multiple models to reduce bias and variance.
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Related literature
ranked by community starsMechanism-informed probabilistic surrogate modeling for maglev train-bridge interactions: A stacking-guided Residual Gaussian Process approach for risk screeningOpen source
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