AINeutralarXiv – CS AI · 15h ago6/10
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How to Square Tensor Networks and Circuits Without Squaring Them
Researchers have developed new parameterization methods for squared tensor networks and circuits that eliminate computational overhead in marginalization and partition function calculations. By leveraging unitary matrix parameterizations inspired by orthogonality and determinism principles, the approach maintains expressiveness while enabling more efficient machine learning applications without the traditional squaring operation complexity.