The following pages link to PITA (Q19014):
Displaying 22 items.
- The distribution semantics for normal programs with function symbols (Q313122) (← links)
- \(T_{\mathcal{P}}\)-compilation for inference in probabilistic logic programs (Q324656) (← links)
- Probabilistic (logic) programming concepts (Q894692) (← links)
- Bandit-based Monte-Carlo structure learning of probabilistic logic programs (Q894703) (← links)
- An OpenCL implementation of a forward sampling algorithm for CP-logic (Q900368) (← links)
- Causal inference in cplint (Q1679666) (← links)
- Learning hierarchical probabilistic logic programs (Q2071314) (← links)
- A functional account of probabilistic programming with possible worlds. Declarative pearl (Q2163171) (← links)
- Constructing generative logical models for optimisation problems using domain knowledge (Q2203323) (← links)
- Probabilistic abstract argumentation frameworks, a possible world view (Q2300457) (← links)
- Lifted discriminative learning of probabilistic logic programs (Q2425249) (← links)
- Tabling and answer subsumption for reasoning on logic programs with annotated disjunctions (Q2883089) (← links)
- Constraint-Based Inference in Probabilistic Logic Programs (Q4559821) (← links)
- Viterbi training in PRISM (Q4592976) (← links)
- Structure learning of probabilistic logic programs by searching the clause space (Q4592977) (← links)
- (Q4637032) (← links)
- Probabilistic DL Reasoning with Pinpointing Formulas: A Prolog-based Approach (Q4957185) (← links)
- (Q5020546) (← links)
- Efficient Knowledge Compilation Beyond Weighted Model Counting (Q5038457) (← links)
- MAP Inference for Probabilistic Logic Programming (Q5140005) (← links)
- Inference in probabilistic logic programs using lifted explanations (Q5240217) (← links)
- Learning Effect Axioms via Probabilistic Logic Programming (Q5240229) (← links)
