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GitHub / clementchadebec / benchmark_VAE

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/clementchadebec%2Fbenchmark_VAE

Stars: 1,698
Forks: 154
Open Issues: 24

License: apache-2.0
Language: Python
Repo Size: 42.5 MB
Dependencies: 37

Created: over 2 years ago
Updated: 17 days ago
Last pushed: about 2 months ago
Last synced: 15 days ago

Commit Stats

Commits: 342
Authors: 18
Mean commits per author: 19.0
Development Distribution Score: 0.415
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/clementchadebec/benchmark_VAE

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

Files
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    Readme
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    Dependencies
    examples/notebooks/requirements.txt pypi
    requirements.txt pypi
    setup.py pypi
    .github/workflows/coverage.yml actions
    .github/workflows/tests_bench.yml actions
    docs/requirements.txt pypi