A Causal View on Robustness of Neural Networks

ICLR 2020 Cheng ZhangKun ZhangYingzhen Li

We present a causal view on the robustness of neural networks against input manipulations, which applies not only to traditional classification tasks but also to general measurement data. Based on this view, we design a deep causal manipulation augmented model (deep CAMA) which explicitly models possible manipulations on certain causes leading to changes in the observed effect... (read more)

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