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pytorch-energy-based-model

This repository provides simple illustrative working examples for energy-based models (EBM) in PyTorch.

The aim of the repository is to provide educational resources, to validate each step with toy examples, and to build a platform for future experiment.

Quickstart

The main requirements are python>=3.6 and torch>=1.2.

pip install -r requirements.txt

Validate Langevin dynamics sampling

python run_langevin.py 8gaussians

Training an energy-based model

python run_ebm.py 8gaussians

Expected Results

Directories

  • run_langevin.py : Run Langevin dynamics sampling of a toy distribution. Produces images of samples.
  • run_ebm.py : Train an EBM for a samples from a toy distribution.
  • langevin.py : Codes related to Langevin dynamics
  • model.py : Codes related to neural networks
  • data.py : Codes related to generating toy distributions

Further reading

  • IGEMB
  • LeCun
  • secretely