generative-models and GANVAS-models
These two tools are competitors, as both aim to provide a collection or library of various generative models like GANs and VAEs, offering similar functionalities for synthetic data generation.
About generative-models
wiseodd/generative-models
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Implements 20+ GAN variants (Vanilla, WGAN, InfoGAN, DiscoGAN, etc.) alongside VAE architectures, RBMs, and Helmholtz Machines with contrastive divergence training. Provides dual PyTorch and TensorFlow implementations for each model, enabling framework comparison and cross-framework experimentation. Automatically outputs generated samples to model-specific directories during training, supporting both image generation and representation learning workflows.
About GANVAS-models
MRSAIL-Mini-Robotics-Software-AI-Lab/GANVAS-models
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)
Scores updated daily from GitHub, PyPI, and npm data. How scores work