https://github.com/clementchadebec/benchmark_VAE

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
https://github.com/clementchadebec/benchmark_VAE

benchmarking beta-vae comparison normalizing-flows pixel-cnn pytorch reproducibility reproducible-research vae vae-gan vae-implementation vae-pytorch variational-autoencoder vq-vae wasserstein-autoencoder

Last synced: about 1 month ago
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Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

• Host: GitHub
• URL: https://github.com/clementchadebec/benchmark_VAE
• Owner: clementchadebec
• License: apache-2.0
• Created: 2021-10-02T16:26:24.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2024-07-31T12:13:28.000Z (4 months ago)
• Last Synced: 2024-11-04T17:12:07.732Z (about 1 month ago)
• Topics: benchmarking, beta-vae, comparison, normalizing-flows, pixel-cnn, pytorch, reproducibility, reproducible-research, vae, vae-gan, vae-implementation, vae-pytorch, variational-autoencoder, vq-vae, wasserstein-autoencoder
• Language: Python
• Homepage:
• Size: 42.5 MB
• Stars: 1,814
• Watchers: 18
• Forks: 163
• Open Issues: 30
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Citation: CITATION.cff

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