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… (More)
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Atomic formulaBelief propagationClique (graph theory)Constrained conditional model
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Papers overview

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Highly Cited
2010
Highly Cited
2010
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can… (More)
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Highly Cited
2009
Highly Cited
2009
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as… (More)
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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… (More)
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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… (More)
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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… (More)
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Highly Cited
2007
Highly Cited
2007
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes… (More)
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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… (More)
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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… (More)
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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… (More)
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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… (More)
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