https://github.com/congyewang/harnessing-the-power-of-reinforcement-learning-for-adaptive-mcmc
Harnessing the Power of Reinforcement Learning for Adaptive MCMC
https://github.com/congyewang/harnessing-the-power-of-reinforcement-learning-for-adaptive-mcmc
Science Score: 26.0%
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○Scientific vocabulary similarity
Low similarity (5.1%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Harnessing the Power of Reinforcement Learning for Adaptive MCMC
Basic Info
Statistics
- Stars: 0
- Watchers: 4
- Forks: 0
- Open Issues: 0
- Releases: 0
Created almost 2 years ago
· Last pushed 11 months ago
Metadata Files
Readme
License
README.md
Harnessing the Power of Reinforcement Learning for Adaptive MCMC
Requirement
- Platform
- Ubuntu 22.04.4 LTS x86_64
- Language
- Python 3.12.10
```{bash}
Download Python
uv python install 3.12 uv python pin 3.12
Download Python Packages
uv sync ```
Please note that this project has not been tested in Windows system, consult the Stan and Bridgestan.
License
PyRLMALA is released under the MIT License. See the LICENSE file for details.
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
GitHub Events
Total
- Push event: 17
- Public event: 1
Last Year
- Push event: 17
- Public event: 1
Dependencies
.github/workflows/deploy.yml
actions
- actions/checkout v3 composite
- peaceiris/actions-gh-pages v3 composite
pyproject.toml
pypi
- adaptive-mcmc >=0.1.3
- bridgestan >=2.5.0
- cmdstanpy >=1.2.5
- coverage >=7.6.7
- cytoolz >=1.0.1
- dash >=2.18.2
- duckdb >=1.1.3
- ipywidgets >=8.1.5
- jaxtyping >=0.2.36
- loguru >=0.7.3
- mcmclib *
- mcmctoolbox >=0.20.0
- myst-parser >=4.0.0
- numpy >=2.1.3
- pandas >=2.2.3
- posteriordb >=0.2.0
- prettytable >=3.12.0
- pytest >=8.3.3
- pytest-cov >=6.0.0
- pytest-mock >=3.14.0
- pytorch-ignite >=0.5.1
- scikit-learn >=1.6.1
- scipy >=1.14.1
- sphinx >=8.1.3
- sphinx-autodoc-typehints >=2.5.0
- sphinx-markdown-builder >=0.6.7
- sphinx-rtd-theme >=3.0.2
- stable-baselines3 >=2.3.2
- tensorboard >=2.18.0
- tomli-w >=1.1.0
- torch-tb-profiler >=0.4.3
- tqdm >=4.66.6
- wandb >=0.18.7
- watchdog >=6.0.0
- xarray >=2025.1.1
uv.lock
pypi
- 231 dependencies