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On Probabilistic Inference Through Parametric Tensor Decomposition in Base Tensor Networks
Probabilistic inference is generally only tractable in low-treewidth graphical models, limiting its effective applicability in high-treewidth settings. Many existing methods improve efficiency by exploiting specific parametric structure, such as symmetries. However, they typically require such struc
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