Prospective/current users: please vist the project web page for more information as well as our JSS paper.
Docker image: link to documentation
New feature: Blang can now run on 1000s of machines using MPI via the Pigeons-Blang bridge
Blang developers: in addition to the above resources, see also the documentation repository for more information.
This is one of the repositories hosting Blang's code. This one contains the Blang's SDK (Software Development Kit), including:
- Basic datatypes suitable for sampling.
- Infrastructure to create new data types and distributions.
- Inference algorithms for such datatypes, such as Adaptive Non-Reversible Parallel Tempering and Sequential Change of Measure.
- Standard probability distributions.
- MCMC testing infrastructure.
- Runtime to perform static analysis to infer the factor graph and its sparsity patterns.
- Automated post-processing facilities (MCMC diagnostic, trace/density/pmf/summaries generation, etc).
See this readme for a roadmap of the other key repositories (language infrastructure, examples, supporting libraries, etc)
Citing Blang: if you find Blang useful for your work, consider citing our JSS paper:
Alexandre Bouchard-Côté, Kevin Chern, Davor Cubranic, Sahand Hosseini, Justin Hume, Matteo Lepur, Zihui Ouyang, Giorgio Sgarbi (2022)
Journal of Statistical Software 103:1–98