New feature and minor bugfixes

1. Bugfix in SimulationMemory affecting the use of empty folders for initializing a Trainer;
2. Bugfix in Trainer.train_from_presimulation() for model comparison tasks;
3. Added a classifier two-sample test (C2ST) function c2st in computational_utilities.

Bugfixes and improved documentation

1. Bugfix related to training SetTransformer with induced points
2. Bugfix for offline training of transformers with variable sizes
3. Complete revamp of documentation, README, and tutorials

PyPI Publish

Enable PyPI integration through GitHub workflows.

Beyond Beta!

Following multiple improvements and being actively used in multiple projects, the BayesFlow library is ready to move beyond the beta phase!

Features:

1. Added option for permutation='learnable' when creating an InvertibleNetwork
2. Added option for coupling_design in ["affine", "spline", "interleaved"] when creating an InvertibleNetwork
3. Simplified passing additional settings to the internal networks. For instance, you
   can now simply do
   inference_network = InvertibleNetwork(num_params=20, coupling_net_settings={'mc_dropout': True})
   to get a Bayesian neural network.
4. PMPNetwork has been added for model comparison according to findings in https://arxiv.org/abs/2301.11873
5. Publication-ready calibration diagnostic for expected calibration error (ECE) in a model comparison setting has been
   added to diagnostics.py and is accessible as plot_calibration_curves()
6. A new module experimental has been added currently containing rectifiers.py.
7. Default settings for transformer-based architectures.
8. Numerical calibration error using posterior_calibration_error()

General Improvements:

1. Improved docstrings and consistent use of keyword arguments vs. configuration dictionaries
2. Increased focus on transformer-based architectures as summary networks
3. Figures resulting diagnostics.py have been improved and prettified
4. Added a module sensitivity.py for testing the sensitivity of neural approximators to model misspecification
5. Multiple bugfixes, including a major bug affecting the saving and loading of learnable permutations

The project now also features automatic PyPI publishing. :)

BayesFlow Future is Here!

Welcome to the Future!