Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning
Andrew Bond, Zafer Dogan
The files oja.py, past.py, petrels.py, grouse.py, and gan.py all contain the empirical implementations of the different algorithms. The simulations can be run with the simulations.py file.
For testing specifically on the eigenfaces (Olivetti Faces) dataset, the eigenface_training.ipynb jupyter notebook can be used.
The relevant ODEs are implemented in the ode_different_dims.py and ode.py files, depending on which version you want to use. You can run the comparison of ODE vs GAN model using the training.py file.
