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sgmcmc_preferential_subsampling

Code for Preferential Subsampling for Stochastic Gradient Langevin Dynamics

For full details, please refer to the arXiv preprint of this work.

All code is written in Python 3.7x and the key list of module requirements are provided in requirements.txt.

Run ./setup.sh to set up the data/ folder. This will generate all synthetic data and download the real data used in this paper.

The source code for both models and samplers can be found in the src/ folder.

All experiments can be found in the experiments/ folder. Jupyter Notebooks for each experiment should be opened within their containing folder. Each experiment folder contains a Description.txt file which details the purpose of each notebook.

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