stein-pi-importance-sampling
Stein Pi-Importance-Sampling
Science Score: 44.0%
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Stein Pi-Importance-Sampling
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Metadata Files
README.md
Stein Pi-Importance-Sampling
This code accompanies the paper "Stein $\Pi$-Importance Sampling". It was written in Python 3.10.4 and also tested in Python 3.10.4.
This package can be installed directly by pip in the root directory
bash
python -m pip install .
Some of the experiments in this paper rely on the following packages
- Stein Thinning
- posteriordb v0.4.0
- posteriordb-python
- BridgeStan v1.0.2
- qpsolvers v3.4.0
- proxsuite v0.3.7
- Wasserstein v1.1.0
The original package for Stein Thinning has been modified, and it can be installed in the following way
bash
cd stein_thinning
python -m pip install .
To reproduce the experiment, first navigate to the "experiment" folder
bash
cd experiment
and then clone the posteriordb using
bash
git clone https://github.com/stan-dev/posteriordb.git
run the relevant script finally. e.g. "genestorewksd.py" will run the benchmarking on PosteriorDB to store the numpy data files. "plot_KSDCurve.py" will plot the corresponding results.
Owner
- Name: Congye
- Login: congyewang
- Kind: user
- Location: Newcastle upon Tyne
- Company: Newcastle University
- Repositories: 1
- Profile: https://github.com/congyewang
PhD Candidate in Statistics at Newcastle University
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this work, please cite it as below."
authors:
- family-names: "Wang"
given-names: "Congye"
- family-names: "Chen"
given-names: "Ye"
- family-names: "Kanagawa"
given-names: "Heishiro"
- family-names: "Oates"
given-names: "Chris J"
title: "Stein $\\Pi$-Importance Sampling"
version: "1.0.0"
date-released: "2024-01-01"
url: "https://github.com/congyewang/Stein-Pi-Importance-Sampling"
preferred-citation:
type: article
authors:
- family-names: "Wang"
given-names: "Congye"
- family-names: "Chen"
given-names: "Ye"
- family-names: "Kanagawa"
given-names: "Heishiro"
- family-names: "Oates"
given-names: "Chris J"
journal: "Advances in Neural Information Processing Systems"
title: "Stein $\\Pi$-Importance Sampling"
volume: 36
year: 2024
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