Inducing Causal Structure for Interpretable Neural Networks

Atticus Geiger, Zhengxuan Wu, Hanson Lu +5

In many areas, we have well-founded insights about causal structure that would be useful to bring into our trained models while still allowing them to learn in a data-driven fashio…