Sbi

API change

- We have moved `sbi` to an new github organization: `https://github.com/sbi-dev/sbi`
- We have changed the website of the `sbi` docs: `https://sbi-dev.github.io/sbi/`.
- `sbi.analysis.pairplot`: `upper` was replaced by `offdiag` and will be deprecated in a future release.

Features and enhancements
- size-invariant embedding nets for amortized inference with iid-data (janfb, 808)
- option for new using MAF with rational quadratic splines (thanks to ImahnShekhzadeh, 819)
- improved docstring for `process_prior` (thanks to musoke, 813)
- extended tutorial for SBI with iid data (janfb, 857)
- new tutorial for SBI with experimental conditions and mixed data (janfb, 829)
- New options for `pairplot`:
- `upper` is now called `offdiag` to match other kwargs.
- alternating colors for `samples` and `points`
- option to add a `legend` and pass `kwargs` for the legend.

Bug fixes

- fixed memory leak in in `append_simulations` (thanks to VictorSven, 803)
- bug fix for CNRE (thanks to bkmi, 815)
- bug fix for iid-inference with posterior ensembles (janfb, 826)
- bug fix for simulation-based calibration with VI posteriors (janfb, 834, 838)
- bug fix for BoxUniform device handling (janfb, 854, 856)
- bug fix for MAP estimates with independent priors (janfb, 867)
- bug fix for tutorial on SBC (michaeldeistler, 891)
- fix spurious seeding for `simulate_for_sbi` (jan-matthis, 876)
- bump python version of github action tests to `3.9.13` (michaeldeistler, 888, 900)

- implementation of ["Contrastive Neural Ratio Estimation"](https://openreview.net/forum?id=kOIaB1hzaLe) (thanks to bkmi, #787)
- implementation of ["Balanced Neural Ratio Estimation"](https://openreview.net/forum?id=o762mMj4XK) (thanks to ADelau, #779)
- bugfixes for SBC, device handling and iid-data (793, 789, 780)

Major changes and bug fixes

- implementation of ["Truncated proposals for scalable and hassle-free sbi"](https://openreview.net/forum?id=QW98XBAqNRa) (#754)
- sample-based expected coverage tests (754)
- permutation invariant embedding to allow iid data in SNPE (thanks coschroeder, 751)
- convolutional neural network embedding (thanks coschroeder, 745, 751, 769)
- disallow invalid simulations when using SNLE, SNRE, or atomic SNPE-C (768)

Enhancements

- add tutorial on all available methods (754)
- allow seeding of `simulate_for_sbi` on multiple workers (762)
- expose `enable_transforms` in sampler interface (756)
- bugfix for building the transformation of transformed distributions (756)

- Rely on new version of `pyknos` with bugfix for APT with MDNs (734)
- bugfix: atomic SNPE-C now allows any kind of proposal (732)
- bugfix for SNPE with implicit prior on GPU (730)
- SNPE-A has `force_first_round_loss=True` as default (729)

- bug fix for `ArviZ` integration (727)

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)