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Research map / Probabilistic and scientific modeling / Molecules and proteins

New Liftable Classes for First-Order Probabilistic Inference

NeurIPS 2016 · Probabilistic and scientific modeling › Molecules and proteins · approach: Probabilistic embeddings and relational inference · 19 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add domain recursion rule to standard lifted inference rulesS4 clause, symmetric-transitivity, birthday paradox theory, S2FO2/S2RU theories · domain-liftability (theoretical)domain-liftable (polynomial in domain sizes)Helped
add domain recursion rule (ablation)theory of Example with jobs/volunteers (WFOMC-v3.0 baseline without it) · run-time vs population size nrun-time slope (polynomial degree): slope approximately 4 with domain recursionHelped
add domain recursion rule (ablation)S4 clause · run-time vs population size nrun-time slope (polynomial degree): slope around 5 with domain recursion, vs exponential/grounded baselineHelped
add domain recursion rule (ablation)symmetric-transitivity theory · run-time vs population size nrun-time slope (polynomial degree): slope around 2 with domain recursionHelped
add domain recursion rule to non-symmetric transitivity theorynon-symmetric transitivity (category 3 theory) · theoretical time complexitytime complexityHelped
new classes S2FO2 and S2RU defined as alpha ∧ beta, with beta in FO2 or RU respectivelydomain-liftable classes · theoretical class inclusiondomain-liftable class coverageHelped

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