PHom-GeM: Persistent Homology for Generative Models

Understand

Generative neural network models, including Generative Adversarial Network (GAN) and Auto-Encoders (AE), are among the most popular neural network models to generate adversarial data.

• The GAN model is composed of a generator that produces synthetic data and of a discriminator that discriminates between the generator's output and the true data.
• AE consist of an encoder which maps the model distribution to a latent manifold and of a decoder which maps the latent manifold to a reconstructed distribution.
• However, generative models are known to provoke chaotically scattered reconstructed distribution during their training, and consequently, incomplete generated adversarial distributions.