disentangling-vae
benchmark_VAE
disentangling-vae | benchmark_VAE | |
---|---|---|
1 | 4 | |
766 | 1,687 | |
- | - | |
0.0 | 6.1 | |
over 1 year ago | 27 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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disentangling-vae
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[P] Python library for Variational Autoencoder benchmarking
There is a good repo of different beta-vae models here: https://github.com/YannDubs/disentangling-vae
benchmark_VAE
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Researchers From INRIA France Propose ‘Pythae’: An Open-Source Python Library Unifying Common And State-of-the-Art Generative AutoEncoder (GAE) Implementations
Continue reading | Checkout the paper, github
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[P] Pythae - Unifying generative autoencoder implementations in Python
Code for https://arxiv.org/abs/2206.08309 found: https://github.com/clementchadebec/benchmark_VAE
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[P] Python library for Variational Autoencoder benchmarking
Github link: https://github.com/clementchadebec/benchmark_VAE
- Python library for Variational Autoencoder Benchmarking
What are some alternatives?
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scvi-tools - Deep probabilistic analysis of single-cell and spatial omics data
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nflows - Normalizing flows in PyTorch
minimal_VAE_on_Mario - A minimal VAE trained on Super Mario Bros levels.
cloud_benchmarker - Cloud Benchmarker automates performance testing of cloud instances, offering insightful charts and tracking over time.