kProbLog: an algebraic Prolog for machine learning

DOI10.1007/s10994-017-5668-yzbMath1457.68237OpenAlexW2765974293MaRDI QIDQ1699913

Francesco Orsini, Luc De Raedt, Paolo Frasconi

Publication date: 26 February 2018

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-017-5668-y

zbMATH Keywords

machine learninggraph kernelsalgebraic Prologkernel programming

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic programming (68N17)

Related Items (3)

Semiring programming: a semantic framework for generalized sum product problems ⋮ Beyond graph neural networks with lifted relational neural networks ⋮ Optimizing Probabilities in Probabilistic Logic Programs

Uses Software

• Torch
• Theano
• ProbLog
• kLog
• FPsolve
• TensorFlow
• DiffSharp
• kProbLog
• Datalog
• BLOG
• Dyna
• kFOIL
• PRISM

Cites Work

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• \(T_{\mathcal{P}}\)-compilation for inference in probabilistic logic programs
• ILP turns 20. Biography and future challenges
• kLog: a language for logical and relational learning with kernels
• Kernels and distances for structured data
• Algebraic model counting
• Markov logic networks
• Statistical Relational Artificial Intelligence: Logic, Probability, and Computation
• FPsolve: A Generic Solver for Fixpoint Equations over Semirings
• Logical and Relational Learning
• Evaluating Derivatives
• The Semantics of Predicate Logic as a Programming Language
• Semirings and Formal Power Series
• Learning Theory and Kernel Machines
• Compiling Probabilistic Graphical Models Using Sentential Decision Diagrams
• Programming Languages and Systems

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