Jonas Arruda
This pull request introduces a new gradient-based sampler, the Metropolis-Adjusted Langevin Algorithm (MALA), to the `pypesto.sample` module, and refactors the covariance regularization in the adaptive Metropolis sampler. The changes also...
This pull request introduces compositional sampling support to the BayesFlow framework, enabling diffusion models to handle multiple compositional conditions efficiently. The main changes span the continuous approximator, diffusion model, and...
This pull request introduces a new option to provide a custom time embedding layer to the `StableConsistencyModel` class, improving its flexibility and configurability. This also fixes a bug while loading...
This pull request enhances the `classifier_two_sample_test` diagnostic metric by introducing k-fold cross-validation support.
This pull request introduces significant improvements to the integration utilities, focusing on broader support for stochastic integration methods. The main changes include adding new samplers, refactoring the diffusion model to...
This pull request introduces significant improvements to the optimal transport functionality, with a focus on supporting partial and conditional optimal transport in both the Sinkhorn and Log-Sinkhorn algorithms. * Added...
It would be nice to be able to compute the gradient of the log probability (in the new BayesFlow version). For example, with the jax-backend, I would like to be...