https://github.com/anskarl/lomrf

LoMRF is an open-source implementation of Markov Logic Networks
https://github.com/anskarl/lomrf

graphical-models inference logic machine-learning probabilistic-programming scala

Last synced: 6 days ago
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LoMRF is an open-source implementation of Markov Logic Networks

• Host: GitHub
• URL: https://github.com/anskarl/lomrf
• Owner: anskarl
• License: apache-2.0
• Created: 2014-05-24T22:29:28.000Z (over 10 years ago)
• Default Branch: develop
• Last Pushed: 2024-09-07T19:50:58.000Z (about 2 months ago)
• Last Synced: 2024-09-07T20:47:59.131Z (about 2 months ago)
• Topics: graphical-models, inference, logic, machine-learning, probabilistic-programming, scala
• Language: Scala
• Homepage: https://anskarl.github.io/LoMRF
• Size: 17.5 MB
• Stars: 81
• Watchers: 9
• Forks: 20
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.TXT

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    Logical Markov Random Fields.



# LoMRF: Logical Markov Random Fields

LoMRF is an open-source implementation of [Markov Logic Networks](https://en.wikipedia.org/wiki/Markov_logic_network) (MLNs) written in [Scala programming language](http://scala-lang.org).

## Features overview:

1. Parallel grounding algorithm based on [Akka Actors library](http://akka.io).

2. Marginal (MC-SAT) and MAP (MaxWalkSAT and LP-relaxed Integer Linear Programming) inference (**lomrf infer**).

3. Batch and on-line Weight Learning (Max-Margin, AdaGrad and CDA) (**lomrf wlearn**).

4. On-line Structure Learning (OSL and OSLa) (**lomrf slearn**).

5. MLN knowledge base compilation (**lomrf compile**):

  * Predicate completion.

  * Clausal form transformation.

  * Replacement of functions with utility predicates and vice versa.

  * Reads and produces [Alchemy](http://alchemy.cs.washington.edu/alchemy1.html) compatible MLN files.

6. Can export ground MRF in various formats (**lomrf export**).

7. Can compare MLN theories (**lomrf diff**).

8. Online supervision completion on semi-supervised training sets [*currently experimental*] (**lomrf supervision**)

## Documentation

Latest [documentation](docs/index.md).

## Contributions

Contributions are welcome, for details see [CONTRIBUTING.md](CONTRIBUTING.md).

## License

Copyright (c) 2014 - 2019 Anastasios Skarlatidis and Evangelos Michelioudakis

LoMRF is licensed under the Apache License, Version 2.0: [https://www.apache.org/licenses/LICENSE-2.0](https://www.apache.org/licenses/LICENSE-2.0)

## Reference in Scientific Publications

Please use the following BibTex entry when you cite LoMRF in your papers:

```

@misc{LoMRF,

	author = {Anastasios Skarlatidis and Evangelos Michelioudakis},

	title = {{Logical Markov Random Fields (LoMRF): an open-source implementation of Markov Logic Networks}},

	url = {https://github.com/anskarl/LoMRF},

	year = {2014}

}

```