Author: Alejandro Pozas Kerstjens
Implementation of different generative models based on energy-based learning. Examples are provided with the MNIST dataset.
- pytorch >= 0.4.0 as ML framework
- numpy for math operations
- matplotlib for image visualization
- tqdm for custom progress bar
- imageio for exporting outputs to
Restricted Boltzmann Machine with binary visible and hidden units. Although in this example it is used as a generative model, RBMs can also perform supervised tasks. The current implementation allows for both binary and continuous-valued visible units.
Deep belief network with greedy pre-training plus global finetuning.