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May, 2022
前馈神经网络的因果发现和注入
Causal Discovery and Injection for Feed-Forward Neural Networks
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Fabrizio Russo, Francesca Toni
TL;DR
本文通过向前馈神经网络注入潜在的因果关系，以保证神经网络模型符合专家知识，从而提高模型在发现因果关系和预测性能方面的鲁棒性和精度。
Abstract
neural networks
have proven to be effective at solving a wide range of problems but it is often unclear whether they learn any meaningful
causal relationship
: this poses a problem for the robustness of neural net
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