The repository for STA663 Final Project. Focus on the implementation and optimizaiton of SGHMC sampler.
Here is a brief overview of the repo.
.
├── README.md <-- This instructions file
├── reports
│ ├── report_2song.pdf <-- our final report
| └── 1402.4102.pdf <-- Chen et.al 2014, original paper
├── sghmc <-- sghmc package source code
│ ├── __init__.py
│ ├── preprocess.py <-- data preprocess
| └── sghmc.py <-- sghmc sampler
├── experiments
│ ├── Figure_*.ipynb <-- figures 1-5 in experiments
│ └── bayesnn <-- figure 6, bayes neural network
├── notebooks
│ ├── eigen/ <-- dependencies for optimization
│ ├── Optimization_demo.ipynb <-- optimization work
│ └── Comparative_analysis.ipynb <-- comparative analysis work
├── requirements.txt <-- dependencies you need to run the example
└── setup.py pip install -i https://test.pypi.org/simple/ sghmc-2song- Clone the repository in sta663 server or a similar docker container
git clone https://github.com/JiajunSong629/SGHMC.git
cd SGHMC/- Create the virtural environment and activate. Intall the dependencies and you should see the list of packages installed. sghmc-2song is the one this project implements. Others will be needed in experiment and optimization notebooks.
python3 -m venv .sghmc
source .sghmc/bin/activate
python -m pip install --upgrade pip wheel
pip install -i https://test.pypi.org/simple/ sghmc-2song
pip install -r requirements.txt
pip list- Add the environment for ipython kernel and change kernel to
.sghmcwhen launching the notebook.
python -m ipykernel install --user --name=.sghmc- Add the dependencies to compile C++
cd notebooks/
git clone https://gitlab.com/libeigen/eigen.git