GitHub / EliaFantini / WGAN-learns-the-distributon-of-a-MoG
A Wasserstein Generative Adversarial Network that learns the distribution of a Mixture of Gaussian, using weight clipping or spectral normalization
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PURL: pkg:github/EliaFantini/WGAN-learns-the-distributon-of-a-MoG
Stars: 0
Forks: 0
Open issues: 0
License: None
Language: Python
Size: 24.8 MB
Dependencies parsed at: Pending
Created at: almost 3 years ago
Updated at: almost 3 years ago
Pushed at: almost 3 years ago
Last synced at: about 2 years ago
Topics: anaconda3, data-science, gan, generative-adversarial-network, gif-animation, lipschitz-constant, lipschitz-regularization, machine-learning, matplotlib, minimax-algorithm, mixture-of-gaussians, python, pytorch, spectral-normalization, wasserstein-gan, weight-clip