Data

Tools

Indexes

Applications

Experiments

Open Source Science

InferOpt

Combinatorial optimization layers for machine learning pipelines

https://github.com/juliadecisionfocusedlearning/inferopt.jl

Science Score: 54.0%

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

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: arxiv.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.3%) to scientific vocabulary

Keywords

automatic-differentiation combinatorial-optimization julia machine-learning structured-learning
Last synced: 6 months ago · JSON representation ·

Repository

Combinatorial optimization layers for machine learning pipelines

Basic Info
Statistics
  • Stars: 126
  • Watchers: 3
  • Forks: 4
  • Open Issues: 19
  • Releases: 12
Topics
automatic-differentiation combinatorial-optimization julia machine-learning structured-learning
Created almost 4 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

InferOpt.jl

Stable Dev Build Status Coverage Code Style: Blue Aqua QA

Overview

InferOpt.jl is a toolbox for using combinatorial optimization algorithms within machine learning pipelines.

It allows you to create differentiable layers from optimization oracles that do not have meaningful derivatives. Typical examples include mixed integer linear programs or graph algorithms.

Getting started

To install the stable version, open a Julia REPL and run the following command:

julia julia> using Pkg; Pkg.add("InferOpt")

To install the development version, run this command instead:

julia julia> using Pkg; Pkg.add(url="https://github.com/JuliaDecisionFocusedLearning/InferOpt.jl")

Citing us

If you use our package in your research, please cite the following paper:

Learning with Combinatorial Optimization Layers: a Probabilistic Approach - Guillaume Dalle, Léo Baty, Louis Bouvier and Axel Parmentier (2022)

Related packages

The following libraries implement similar functionalities:

  • ImplicitDifferentiation.jl: automatic differentiation of implicit functions
  • DiffOpt.jl: differentiating convex optimization programs w.r.t. program parameters
  • JAXopt: hardware accelerated, batchable and differentiable optimizers in JAX

Owner

  • Name: JuliaDecisionFocusedLearning
  • Login: JuliaDecisionFocusedLearning
  • Kind: organization

Citation (CITATION.bib) 

@misc{InferOpt.jl,
	author  = {Guillaume Dalle, Léo Baty, Louis Bouvier and Axel Parmentier},
	title   = {InferOpt.jl},
	url     = {https://github.com/axelparmentier/InferOpt.jl},
	version = {v0.7.1},
	year    = {2025},
	month   = {7}
}

GitHub Events

Total
  • Create event: 5
  • Release event: 1
  • Issues event: 5
  • Watch event: 12
  • Delete event: 8
  • Issue comment event: 24
  • Push event: 31
  • Pull request event: 7
Last Year
  • Create event: 5
  • Release event: 1
  • Issues event: 5
  • Watch event: 12
  • Delete event: 8
  • Issue comment event: 24
  • Push event: 31
  • Pull request event: 7

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 60
  • Total pull requests: 83
  • Average time to close issues: 4 months
  • Average time to close pull requests: 29 days
  • Total issue authors: 5
  • Total pull request authors: 6
  • Average comments per issue: 1.52
  • Average comments per pull request: 1.37
  • Merged pull requests: 67
  • Bot issues: 0
  • Bot pull requests: 18
Past Year
  • Issues: 1
  • Pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: about 2 months
  • Issue authors: 1
  • Pull request authors: 3
  • Average comments per issue: 11.0
  • Average comments per pull request: 1.67
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 1
View more stats
Top Authors
Issue Authors
  • gdalle (4)
  • BatyLeo (2)
  • JuliaTagBot (1)
Pull Request Authors
  • BatyLeo (5)
  • dependabot[bot] (3)
  • gdalle (3)
Top Labels
Issue Labels
enhancement (3) bug (1) good first issue (1)
Pull Request Labels
dependencies (3) enhancement (1)

Packages

  • Total packages: 1
  • Total downloads:
    • julia 21 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 12
juliahub.com: InferOpt

Combinatorial optimization layers for machine learning pipelines

  • Versions: 12
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 21 Total
Rankings
Stargazers count: 9.0%
Dependent repos count: 9.9%
Average: 22.8%
Forks count: 33.3%
Dependent packages count: 38.9%
Last synced: 6 months ago

Dependencies

.github/workflows/CI.yml actions
  • actions/checkout v2 composite
  • codecov/codecov-action v2 composite
  • julia-actions/cache v1 composite
  • julia-actions/julia-buildpkg v1 composite
  • julia-actions/julia-docdeploy v1 composite
  • julia-actions/julia-processcoverage v1 composite
  • julia-actions/julia-runtest v1 composite
  • julia-actions/setup-julia v1 composite
.github/workflows/TagBot.yml actions
  • JuliaRegistries/TagBot v1 composite
.github/workflows/register.yml actions
  • julia-actions/RegisterAction latest composite
.github/workflows/CompatHelper.yml actions