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Toward Causal Representation Learning

large, we consider these factors a nuisance and try to engi-neer them away. In accordance with this, the majority of current successes of machine learning boil down to large-scale pattern recognition on suitably collected independent and identically distributed (i.i.d.) data. To illustrate the implications of this choice and its rela-

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