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cs.AI2026
On Probabilistic Inference Through Parametric Tensor Decomposition in Base Tensor Networks
Sagad Hamid, Tanya Braun
Probabilistic inference is generally only tractable in low-treewidth graphical models, limiting its effective applicability in high-treewidth settings. Many existing methods improv…
cs.AI2025
Combining Local Symmetry Exploitation and Reinforcement Learning for Optimised Probabilistic Inference -- A Work In Progress
Sagad Hamid, Tanya Braun
Efficient probabilistic inference by variable elimination in graphical models requires an optimal elimination order. However, finding an optimal order is a challenging combinatoria…