This release includes several improvements, new integrations, and maintenance updates.
Highlights
-
Modernized transformers and deep sets (Breaking)
Updated transformer implementations aligning with modern best-practices for faster convergence and more expressive summary networks. -
PyMC wrapper for Neural Likelihood and Neural Ratio Estimation
Added the long awaited PyMC wrapper supporting Neural Likelihood Estimation and Neural Ratio Estimation out of the box. Plug into any PyMC workflow as easy as:
from bayesflow.wrappers.pymc import NeuralDistribution
# works the same way with ratio or a continuous approximator
pymc_dist = NeuralDistribution(approximator=my_approximator, param_names=["a", "b", "c"])
New tutorials:
-
GLASS sampler for flow matching
Added support for the GLASS sampler in flow matching workflows. -
Improved testing suite
Expanded and improved tests to increase reliability and coverage. -
Minor bug fixes and improvements
Includes smaller fixes, cleanup, and general quality-of-life improvements.