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蔚-commutativity allows for scalable probabilistic inference without sacrificing accuracy, even when learned parameters deviate from exact commutativity.
The standard algorithm for exploiting symmetries in probabilistic inference is broken, potentially leading to incorrect results in lifted inference.
