v0.11.0

• Changed the API to do multi-round inference (#273)
• Allow to continue inference (#273)

v0.10.2

• Added missing type imports (#275)
• Made compatible for Python 3.6 (#275)

v0.10.1

• Added mcmc_parameters to init methods of inference methods (#270)
• Fixed detaching of log_weights when using sir MCMC init (#270)
• Fixed logging for SMC-ABC

v0.10.0

• Added option to pass external data (#264)
• Added setters for MCMC parameters (#267)
• Added check for density_estimator argument (#263)
• Fixed NeuralPosterior pickling error (#265)
• Added code coverage reporting (#269)

v0.9.0

• Added ABC methods (#250)
• Added multiple chains for MCMC and new init strategy (#247)
• Added options for z-scoring for all inference methods (#256)
• Simplified swapping out neural networks (#256)
• Improved tutorials
• Fixed device keyword argument (#253)
• Removed need for passing x-shapes (#259)

First public release

• Check installation instructions.
• Introduction to simulation-based inference, a practical tutorial and full API documentation all available at mackelab.org/sbi.
• We are very grateful to Vinta Chen (@vinta, https://github.com/vinta) for kindly ceding to us the sbi project name on PyPI.