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Workshop

Causal Discovery Using Proxy Variables

Mateo Rojas-Carulla · Marco Baroni · David Lopez-Paz

East Meeting Level 8 + 15 #12

Thu 3 May, 11 a.m. PDT

In this paper, we develop a framework to estimate the cause-effect relation between two static entities x and y: for instance, an art masterpiece x and its fraudulent copy y. To this end, we introduce the notion of proxy variables, which allow the construction of a pair of random entities (A,B) from the pair of static entities (x,y). Then, estimating the cause-effect relation between A and B using an observational causal discovery algorithm leads to an estimation of the cause-effect relation between x and y. We evaluate our framework in vision and language.

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