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Toward Causal Representation Learning - Harvard University
Physical Realism While Retaining the Power to Answer Certain Interventional or Counterfactual Questions data augmentation, and pretraining. We discuss examples at the intersection between causality and machine learning in scientific applications and spec-ulate on the advantages of combining the strengths of both fields to build a more ...
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