Don't PourCerealintoCoffee: Differentiable TemporalLogicforTemporalActionSegmentation

Neural Information Processing Systems 

We propose Differentiable Temporal Logic (DTL), a model-agnostic framework that introduces temporal constraints to deep networks. DTL treats the outputs of a network as a truth assignment of a temporal logic formula, and computes a temporal logic loss reflecting the consistency between the output and the constraints.

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