Learning Loworder Models for Enforcing Highorder Statistics Patrick Pletscher Pushmeet Kohli ETH Zurich Zurich Switzerland Microsoft Research Cambridge UK Abstract Models such as pairwise conditional
However they have limited expressive power and often cannot represent the posterior distribution correctly While learning the parameters of such models which have insu64259cient expressivity researchers use loss functions to penalize certain misrepr
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