anskarl / Lomrf
Licence: apache-2.0
LoMRF is an open-source implementation of Markov Logic Networks
Stars: ✭ 73
Programming Languages
scala
5932 projects
Projects that are alternatives of or similar to Lomrf
typeql
TypeQL: the query language of TypeDB - a strongly-typed database
Stars: ✭ 157 (+115.07%)
Mutual labels: logic, inference
Openllet
Openllet is an OWL 2 reasoner in Java, build on top of Pellet.
Stars: ✭ 66 (-9.59%)
Mutual labels: logic, inference
Turbotransformers
a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.
Stars: ✭ 826 (+1031.51%)
Mutual labels: inference
Multi Model Server
Multi Model Server is a tool for serving neural net models for inference
Stars: ✭ 770 (+954.79%)
Mutual labels: inference
Ncnn Benchmark
The benchmark of ncnn that is a high-performance neural network inference framework optimized for the mobile platform
Stars: ✭ 70 (-4.11%)
Mutual labels: inference
Digital
A digital logic designer and circuit simulator.
Stars: ✭ 1,108 (+1417.81%)
Mutual labels: logic
Bmw Classification Inference Gpu Cpu
This is a repository for an image classification inference API using the Gluoncv framework. The inference REST API works on CPU/GPU. It's supported on Windows and Linux Operating systems. Models trained using our Gluoncv Classification training repository can be deployed in this API. Several models can be loaded and used at the same time.
Stars: ✭ 27 (-63.01%)
Mutual labels: inference
Zipperposition
An automatic theorem prover in OCaml for typed higher-order logic with equality and datatypes, based on superposition+rewriting; and Logtk, a supporting library for manipulating terms, formulas, clauses, etc.
Stars: ✭ 46 (-36.99%)
Mutual labels: logic
Xnnpack
High-efficiency floating-point neural network inference operators for mobile, server, and Web
Stars: ✭ 808 (+1006.85%)
Mutual labels: inference
People Counter Python
Create a smart video application using the Intel Distribution of OpenVINO toolkit. The toolkit uses models and inference to run single-class object detection.
Stars: ✭ 62 (-15.07%)
Mutual labels: inference
Awesome Ml Demos With Ios
The challenge projects for Inferencing machine learning models on iOS
Stars: ✭ 741 (+915.07%)
Mutual labels: inference
Ts Pattern
🎨 A complete Pattern Matching library for TypeScript, with smart type inference.
Stars: ✭ 854 (+1069.86%)
Mutual labels: inference
Opencv Mtcnn
An implementation of MTCNN Face detector using OpenCV's DNN module
Stars: ✭ 59 (-19.18%)
Mutual labels: inference
Neuropod
A uniform interface to run deep learning models from multiple frameworks
Stars: ✭ 858 (+1075.34%)
Mutual labels: inference
o o o o o
| o | |\ /| | /
| o-o o--o o-o oo | | O | oo o-o OO o-o o o
| | | | | | | | | | | | | | | | \ | | \ /
O---oo-o o--O | o-o o-o-o o o o-o-o o o o-o o
|
o--o
o--o o o--o o o
| | | | o | |
O-Oo oo o-o o-O o-o o-O-o O-o o-o | o-O o-o
| \ | | | | | | | | | | | | | |-' | | | \
o o o-o-o o o-o o-o o o o o | o-o o o-o o-o
Logical Markov Random Fields.
LoMRF: Logical Markov Random Fields
LoMRF is an open-source implementation of Markov Logic Networks (MLNs) written in Scala programming language.
Features overview:
- Parallel grounding algorithm based on Akka Actors library.
- Marginal (MC-SAT) and MAP (MaxWalkSAT and LP-relaxed Integer Linear Programming) inference (lomrf infer).
- Batch and on-line Weight Learning (Max-Margin, AdaGrad and CDA) (lomrf wlearn).
- On-line Structure Learning (OSL and OSLa) (lomrf slearn).
- MLN knowledge base compilation (lomrf compile):
- Predicate completion.
- Clausal form transformation.
- Replacement of functions with utility predicates and vice versa.
- Reads and produces Alchemy compatible MLN files.
- Can export ground MRF in various formats (lomrf export).
- Can compare MLN theories (lomrf diff).
- Online supervision completion on semi-supervised training sets [currently experimental] (lomrf supervision)
Documentation
Latest documentation.
Contributions
Contributions are welcome, for details see 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
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}
}
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].