AntixK/PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
Implements 16+ VAE variants (Beta-VAE, VQ-VAE, IWAE, InfoVAE, etc.) with standardized architectures for direct comparison, trained on CelebA for reproducibility. Integrates with PyTorch Lightning for training orchestration and uses YAML configuration files to specify model hyperparameters, dataset paths, and trainer settings. Supports TensorBoard visualization and enables custom kernel choices (RBF, IMQ) for Wasserstein autoencoders.
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Apache-2.0
Last pushed
Mar 21, 2025
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