Probabilistic (logic) programming concepts
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Publication:894692
DOI10.1007/s10994-015-5494-zzbMath1346.68050arXiv1312.4328OpenAlexW811924890MaRDI QIDQ894692
Publication date: 2 December 2015
Published in: Machine Learning (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1312.4328
statistical relational learningprobabilistic logic programmingprobabilistic programming languagesinference in probabilistic languages
Related Items (24)
Learning Probabilistic Logic Programs over Continuous Data ⋮ A survey of lifted inference approaches for probabilistic logic programming under the distribution semantics ⋮ The distribution semantics for normal programs with function symbols ⋮ \(T_{\mathcal{P}}\)-compilation for inference in probabilistic logic programs ⋮ Explanations as programs in probabilistic logic programming ⋮ Forecasting with jury-based probabilistic argumentation ⋮ An Asymptotic Analysis of Probabilistic Logic Programming, with Implications for Expressing Projective Families of Distributions ⋮ Explainable acceptance in probabilistic and incomplete abstract argumentation frameworks ⋮ Asymptotic elimination of partially continuous aggregation functions in directed graphical models ⋮ Implementing a Library for Probabilistic Programming Using Non-strict Non-determinism ⋮ Lifted discriminative learning of probabilistic logic programs ⋮ A landscape and implementation framework for probabilistic rough sets using \textsc{ProbLog} ⋮ Answer-set programs for reasoning about counterfactual interventions and responsibility scores for classification ⋮ Learning Effect Axioms via Probabilistic Logic Programming ⋮ A semantics for hybrid probabilistic logic programs with function symbols ⋮ Neural probabilistic logic programming in DeepProbLog ⋮ Unnamed Item ⋮ Using SWISH to Realize Interactive Web-based Tutorials for Logic-based Languages ⋮ A general approach to reasoning with probabilities ⋮ Probabilistic abstract argumentation frameworks, a possible world view ⋮ Incremental reasoning in probabilistic signal temporal logic ⋮ P-log: refinement and a new coherency condition ⋮ A comparison of statistical relational learning and graph neural networks for aggregate graph queries ⋮ On the Efficient Execution of ProbLog Programs
Uses Software
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