JuliaDecisionFocusedLearning/InferOpt.jl
Combinatorial optimization layers for machine learning pipelines
This tool helps machine learning engineers and researchers integrate complex combinatorial optimization problems, like mixed-integer linear programs or graph algorithms, directly into their machine learning models. It takes an optimization problem's definition and outputs a 'differentiable layer' that can be trained end-to-end within a larger machine learning system. This allows for unified training of both predictive and prescriptive components.
130 stars.
Use this if you are a machine learning engineer or researcher looking to build an end-to-end system that combines a machine learning model with a combinatorial optimization problem, where you want to train both components jointly.
Not ideal if you are looking for a standalone combinatorial optimization solver or a library for general-purpose machine learning, as its specific focus is on creating differentiable optimization layers.
Stars
130
Forks
4
Language
Julia
License
MIT
Category
Last pushed
Nov 24, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/JuliaDecisionFocusedLearning/InferOpt.jl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
CliMA/Oceananigans.jl
🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
JuliaLang/julia
The Julia Programming Language
WassimTenachi/PhySO
Physical Symbolic Optimization
FluxML/Flux.jl
Relax! Flux is the ML library that doesn't make you tensor
EnzymeAD/Enzyme.jl
Julia bindings for the Enzyme automatic differentiator