v0.19.0

Major changes and bug fixes

• new option to sample posterior using importance sampling (#692)
• new option to use arviz for posterior plotting and MCMC diagnostics (#546, #607, thanks to @sethaxen)
• fixes for using the VIPosterior with MultipleIndependent prior, a51e93b
• bug fix for sir (sequential importance reweighting) for MCMC initialization (#692)
• bug fix for SNPE-A 565082c
• bug fix for validation loader batch size (#674, thanks to @bkmi)
• small bug fixes for pairplot and MCMC kwargs

Enhancements

• improved and new tutorials:
  • Tutorial for simulation-based calibration (SBC) (#629, thanks to @psteinb)
  • Tutorial for sampling the conditional posterior (#667)
• new option to use first-round loss in all rounds
• simulated data is now stored as Dataset to reduce memory load and add flexibility
  with large data sets (#685, thanks to @tbmiller-astro)
• refactoring of summary write for better training logs with tensorboard (#704)
• new option to find peaks of 1D posterior marginals without gradients (#707, #708, thanks to @Ziaeemehr)
• new option to not use parameter transforms in DirectPosterior for more flexibility with custom priors (#714)