The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/49f4ee70-a95a-4804-bced-7d2a1a05a656

Pieper, Thorben (2025): Code underlying the publication: Guided filtering and smoothing for infinite-dimensional diffusions. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/49f4ee70-a95a-4804-bced-7d2a1a05a656.v1

Categories

• Statistics
• Mathematical Sciences

Keywords

Data assimilation Doob’s h-transform Exponential change of measure Guided particle filter Infinite-dimensional diffusions Markov chain Monte Carlo Parameter estimation Smoothing Stochastic Amari equation Stochastic partial differential equations.

Licence

CC BY 4.0

Interoperability

• RO-Crate Metadata

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by Thorben Pieper

Code to run the experiments in Pieper-Sethmacher et al. (2025) Guided filtering and smoothing for infinite-dimensional diffusions, arXiv preprint, arXiv:2507.06786.

The Julia source code, GuidedFiltering.jl and GuidedSmoothing.jl, implement Algorithms 1&2 and Algorithm 5. Executing the driver files in the experiments folders runs the experiments of examples in section 5.2 and 5.3 of the article.

History

• 2025-07-11 first online, published, posted

Publisher

4TU.ResearchData

Format

.jl

Associated peer-reviewed publication

Guided filtering and smoothing for infinite-dimensional diffusions

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft Institute for Applied Mathematics