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A theory of independent mechanisms for extrapolation in generative models. (arXiv:2004.00184v2 [cs.LG] UPDATED)
Jan. 3, 2022, 2:10 a.m. | Michel Besserve, Rémy Sun, Dominik Janzing, Bernhard Schölkopf
cs.LG updates on arXiv.org arxiv.org
Generative models can be trained to emulate complex empirical data, but are
they useful to make predictions in the context of previously unobserved
environments? An intuitive idea to promote such extrapolation capabilities is
to have the architecture of such model reflect a causal graph of the true data
generating process, such that one can intervene on each node independently of
the others. However, the nodes of this graph are usually unobserved, leading to
overparameterization and lack of identifiability of the …
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