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Markov logic network

Known as: MLN (disambiguation), Markov logic, Markov logic networks 
A Markov logic network (MLN) is a probabilistic logic which applies the ideas of a Markov network to first-order logic, enabling uncertain inference… Expand
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Related topics

Related topics

19 relations
Atomic formulaBelief propagationClique (graph theory)Constrained conditional model
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2011
Highly Cited
2011
Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS
Markov Logic Networks (MLNs) have emerged as a powerful framework that combines statistical and logical reasoning; they have been… Expand
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Highly Cited
2009
Highly Cited
2009
Markov Logic: An Interface Layer for Artificial Intelligence
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this… Expand
Highly Cited
2008
Highly Cited
2008
Hybrid Markov Logic Networks
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty… Expand
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Highly Cited
2008
Highly Cited
2008
Event Modeling and Recognition Using Markov Logic Networks
We address the problem of visual event recognition in surveillance where noise and missing observations are serious problems… Expand
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Highly Cited
2008
Highly Cited
2008
Discriminative structure and parameter learning for Markov logic networks
Markov logic networks (MLNs) are an expressive representation for statistical relational learning that generalizes both first… Expand
Highly Cited
2007
Highly Cited
2007
Efficient Weight Learning for Markov Logic Networks
Markov logic networks (MLNs) combine Markov networks and first-order logic, and are a powerful and increasingly popular… Expand
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Highly Cited
2006
Highly Cited
2006
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A… Expand
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Highly Cited
2006
Highly Cited
2006
Entity Resolution with Markov Logic
Entity resolution is the problem of determining which records in a database refer to the same entities, and is a crucial and… Expand
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Highly Cited
2005
Highly Cited
2005
Discriminative Training of Markov Logic Networks
Many machine learning applications require a combination of probability and first-order logic. Markov logic networks (MLNs… Expand
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Highly Cited
2005
Highly Cited
2005
Learning the structure of Markov logic networks
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as… Expand
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