# dotnet/infer

Infer.NET is a framework for running Bayesian inference in graphical models

Repository: https://github.com/dotnet/infer
Canonical: https://ross.abutalabs.com/products/dotnet-infer
Homepage: https://dotnet.github.io/infer/
Language: C#
License: MIT
License Family: permissive
Topics: machine-learning, bayesian-inference
Last push: 2026-07-14T18:55:50+00:00

## Health v2 (maintenance only)
Score: 74/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 92, release rhythm 35, longevity 100
- inputs: {"age_days": 2910, "days_push": 50, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1615, forks 242 (observed 2026-08-28T04:05:11.550479+00:00)

## What it is
Infer.NET is a .NET framework for running Bayesian inference in graphical models, also usable for probabilistic programming. It compiles model descriptions written via its API into inference code and ships as cross-platform NuGet packages.

## Use cases
- run bayesian inference on graphical models in .NET
- build a classifier in C#
- build a recommender system with probabilistic modeling
- cluster data with mixture of gaussians
- write probabilistic programs for custom machine learning models
- solve domain-specific inference problems in bioinformatics or epidemiology

## When to choose
- you work in the .NET ecosystem and need probabilistic/Bayesian modeling
- you need custom graphical models rather than off-the-shelf ML
- you want a mature MIT-licensed inference framework with cross-platform NuGet packages

## When to avoid
- you need deep learning or GPU-accelerated training
- your stack is Python-first and PyMC/Pyro/NumPyro would suffice
- you need a rapidly evolving project with frequent releases

## Facets
- artifact type: framework
- maturity: maintenance
- function: machine-learning, data-science
- domain: machine-learning, data-science
- platform: dotnet, cross-platform, windows
- tags: bayesian-inference, probabilistic-programming, graphical-models, csharp, algorithms, linux, macos

## Member repositories
- dotnet/infer (main) score 74

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:11.550479+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:50:17.050817+00:00, confidence not recorded.
  - readme: https://github.com/dotnet/infer (fetched 2026-08-28T04:05:11.550479+00:00, sha 5e44b1b2aee5)
  - homepage: https://dotnet.github.io/infer/ (fetched 2026-08-29T11:22:28.406368+00:00, sha d5f28cf0ab52)
- Data as of 2026-08-30T08:39:29.467469+00:00.