Sbi

Major changes

- New API for specifying sampling methods (487). Old syntax:

python
posterior = inference.build_posterior(sample_with_mcmc=True)


New syntax:

python
posterior = inference.build_posterior(sample_with="mcmc") or "rejection"


- Rejection sampling for likelihood(-ratio)-based posteriors (487)
- MCMC in unconstrained and z-scored space (510)
- Prior is now allowed to lie on GPU. The prior has to be on the same device as the one
passed for training (519).
- Rejection-ABC and SMC-ABC now return the accepted particles / parameters by default,
or a KDE fit on those particles (`kde=True`) (525).
- Fast analytical sampling, evaluation and conditioning for `DirectPosterior` trained
with MDNs (thanks jnsbck 458).

Minor changes

- `scatter` allowed for diagonal entries in pairplot (510)
- Changes to default hyperparameters for `SNPE_A` (thanks famura, 496, 497)
- bugfix for `within_prior` checks (506)

Major changes

- Implementation of SNPE-A (thanks famura and theogruner, 474, 478, 480, 482)
- Option to do inference over iid observations with SNLE and SNRE (484, 488)

Minor changes

- Fixed unused argument `num_bins` when using `nsf` as density estimator (465)
- Fixes to adapt to the new support handling in `torch` `v1.8.0` (469)
- More scalars for monitoring training progress (thanks psteinb 471)
- Fixed bug in `minimal.py` (thanks psteinb, 485)
- Depend on `pyknos` `v0.14.2`

- add option to pass `torch.data.DataLoader` kwargs to all inference methods (thanks narendramukherjee, 445)
- fix bug due to release of `torch` `v1.8.0` (451)
- expose `leakage_correction` parameters for `log_prob` correction in unnormalized
posteriors (thanks famura, 454)

Major changes

- Active subspaces for sensitivity analysis (394, [tutorial](https://sbi-dev.github.io/sbi/tutorial/09_sensitivity_analysis/))
- Method to compute the maximum-a-posteriori estimate from the posterior (412)

API changes

- `pairplot()`, `conditional_pairplot()`, and `conditional_corrcoeff()` should now be imported from `sbi.analysis` instead of `sbi.utils` (394).
- Changed `fig_size` to `figsize` in pairplot (394).
- moved `user_input_checks` to `sbi.utils` (430).

Minor changes

- Depend on new `joblib=1.0.0` and fix progress bar updates for multiprocessing (421).
- Fix for embedding nets with `SNRE` (thanks adittmann, 425).
- Is it now optional to pass a prior distribution when using SNPE (426).
- Support loading of posteriors saved after `sbi v0.15.0` (427, thanks psteinb).
- Neural network training can be resumed (431).
- Allow using NSF to estimate 1D distributions (438).
- Fix type checks in input checks (thanks psteinb, 439).
- Bugfix for GPU training with SNRE_A (thanks glouppe, 442).

- Fixup for conditional correlation matrix (thanks JBeckUniTb, 404)
- z-score data using only the training data (411)

- Small fix for SMC-ABC with semi-automatic summary statistics (402)