> ## Documentation Index
> Fetch the complete documentation index at: https://fpde-80-mintlify-48090872.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Week of June 8, 2026

> Bayesian-FPDE builds a posterior over lambda_hyb candidates, and a new optional plotting module visualizes FPDE attributions out of the box.

## New features

**Bayesian-FPDE.** Build a posterior over `lambda_hyb` candidates instead of picking a single value. Call `FPDEEngine.select_bayesian_lambda` to get a posterior mean, MAP estimate, and credible interval. Then use `explain_one_bayesian` or `explain_batch_bayesian` to produce attributions under the posterior mean. Reach for this when you want model-averaged Hyb-FPDE explanations with uncertainty over the mixture weight. See [Select lambda](/select-lambda) and the [API reference](/api-reference).

**Plotting helpers.** A new optional plotting module visualizes FPDE attributions with bar, waterfall, beeswarm, and scatter plots. It also covers prototype similarity distributions and perturbation curves. Install it with `pip install "fpde[plot]"`, then import from `fpde` or `fpde.plots`. See the [quickstart](/quickstart) for examples.

## Updates

**Example notebook refresh.** A focused `plot_fpde_example.ipynb` replaces the legacy MNIST notebook. It walks through fitting an engine, generating explanations, and producing the new plots end to end.