Tutorials demonstrating Bayesian inference and particle filtering with Sequince.
Example scripts and their explanations live together under examples/.
The tutorials are collected in the documentation, with plots from the example scripts. See the contributing guidelines for instructions on building the documentation locally.
Bug reports, feature requests, and pull requests are welcome via the GitHub repository. Please see the contributing guidelines and AI policy.
The following repositories are part of the sequince ecosystem:
sequince: the main sampling frameworksequince-density: density estimation and preconditioningsequince-bilby: interfaces for using Sequince samplers with Bilbyorng: cross-backend random number generationacai: array-API compatible control flow and iteration
Licensed under the MIT License.