https://github.com/coin-or/gravity

Mathematical Modeling for Optimization and Machine Learning

https://github.com/coin-or/gravity

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
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  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.6%) to scientific vocabulary

Keywords

machine-learning modeling-tool optimization-tools
Last synced: 6 months ago · JSON representation

Repository

Mathematical Modeling for Optimization and Machine Learning

Basic Info
  • Host: GitHub
  • Owner: coin-or
  • License: bsd-3-clause
  • Language: C++
  • Default Branch: master
  • Homepage: https://www.gravityopt.com
  • Size: 299 MB
Statistics
  • Stars: 151
  • Watchers: 20
  • Forks: 31
  • Open Issues: 0
  • Releases: 9
Topics
machine-learning modeling-tool optimization-tools
Created over 9 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

License Github Actions Code Coverage download

Chat on Slack

Mathematical Modeling for Optimization and Machine Learning

www.gravityopt.com

Citing

The original paper was presentend at the Machine Learning Open Source Software Workshop at NeurIPS 2018, a longer version of the paper can be downloaded here.

Bibtex ref: @article{Gravity, title={Gravity: A Mathematical Modeling Language for Optimization and Machine Learning}, author={Hassan Hijazi and Guanglei Wang and Carleton Coffrin}, journal={Machine Learning Open Source Software Workshop at NeurIPS 2018}, year={2018}, note = {Available at \url{www.gravityopt.com}.}, publisher={The Thirty-second Annual Conference on Neural Information Processing Systems (NeurIPS)} }

Getting Started

First, you will need to install an IDE, I recommend to choose among the following:

Visual Studio | Clion | Xcode | Eclipse :-------------------------:|:-------------------------:|:-------------------------:|:-------------------------: | | |

Then, follow the instructions presented in INSTALL.md.

After building, the Gravity library can be found under Gravity/lib, and the executables (from Gravity/examples) can be found under Gravity/bin/Release

The model below was implemented in Xcode:

cover-example

Some Numerical Results:

Performance Profile on ACOPF

The first figure below is a performance profile illustrating percentage of instances solved as a function of time. The figure compares Gravity, JuMP and AMPL's NL interface (used by AMPL and Pyomo) on all standard instances found in the PGLIB benchmark library.

Performance Profile on ACOPF

The figure below compares model build time between Gravity and JuMP on the PGLIB benchmarks.

Model Build Time on ACOPF


Performance Profile on Inverse Ising Model

Performance Profile on Inverse Ising

License

Gravity is licensed under the BSD 3-Clause License. Please see the LICENSE file for details.

Contributors

See the list of contributors here

Owner

  • Name: COIN-OR Foundation
  • Login: coin-or
  • Kind: organization
  • Email: info@coin-or.org
  • Location: United States of America

Computational Infrastructure for Operations Research.

GitHub Events

Total
  • Watch event: 8
  • Fork event: 1
Last Year
  • Watch event: 8
  • Fork event: 1

Dependencies

.github/workflows/cmake.yml actions
  • actions/checkout v2 composite
  • actions/checkout v1 composite
  • codecov/codecov-action v2.1.0 composite
  • egor-tensin/setup-mingw v2 composite
docs/requirements.txt pypi
  • myst_parser *