论文标题
关于因果发现的高斯可能性得分的陷阱
On the pitfalls of Gaussian likelihood scoring for causal discovery
论文作者
论文摘要
我们考虑基于结构因果模型中因果发现的可能性得分方法。特别是，我们专注于高斯评分，并分析模型错误指定的效果，以非高斯误差分布。我们对高斯可能性评分与非参数回归方法的评分表示了令人惊讶的负面结果。
We consider likelihood score-based methods for causal discovery in structural causal models. In particular, we focus on Gaussian scoring and analyze the effect of model misspecification in terms of non-Gaussian error distribution. We present a surprising negative result for Gaussian likelihood scoring in combination with nonparametric regression methods.
