Structure-agnostic Causal Representation Learning
Causal representation learning aims to discover robust features by exploiting the causal structure underlying data generation. Existing methods require specifying the causal structure a priori, yet different structures demand fundamentally incompatible invariance constraints, and misspecification leads to representatio...
Arman Behnam, Bing-Hui Wang
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