benchmark_VAE VS Awesome-VAEs

Compare benchmark_VAE vs Awesome-VAEs and see what are their differences.

benchmark_VAE

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022) (by clementchadebec)
vae Benchmarking beta-vae Comparison normalizing-flows pixel-cnn Pytorch Reproducibility reproducible-research vae-gan vae-implementation vae-pytorch variational-autoencoder vq-vae wasserstein-autoencoder
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Awesome-VAEs

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models. (by matthewvowels1)
vae variational-autoencoder awesome-list disentanglement disentangled-representations representation-learning Deep Learning generative-model unsupervised-learning variational-inference variational-auto-encoder variational-bayes
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benchmark_VAE Awesome-VAEs
4 1
1,695 755
- -
6.1 0.0
about 1 month ago almost 3 years ago
Python
Apache License 2.0 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

benchmark_VAE

Posts with mentions or reviews of benchmark_VAE. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-08.

Awesome-VAEs

Posts with mentions or reviews of Awesome-VAEs. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-29.
  • VAEs
    2 projects | /r/deeplearning | 29 Aug 2021
    List of VAE projects/works: https://github.com/matthewvowels1/Awesome-VAEs

What are some alternatives?

When comparing benchmark_VAE and Awesome-VAEs you can also consider the following projects:

PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.

scvi-tools - Deep probabilistic analysis of single-cell and spatial omics data

awesome-datascience - :memo: An awesome Data Science repository to learn and apply for real world problems.

fastero - Python timeit CLI for the 21st century! colored output, multi-line input with syntax highlighting and autocompletion and much more!

awesome-self-supervised-speech-representation-learning - A comprehensive list of awesome self-supervised speech representation learning papers.

disentangling-vae - Experiments for understanding disentanglement in VAE latent representations

SimCLR - PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

nflows - Normalizing flows in PyTorch

cloud_benchmarker - Cloud Benchmarker automates performance testing of cloud instances, offering insightful charts and tracking over time.

stanford-cs-229-machine-learning - VIP cheatsheets for Stanford's CS 229 Machine Learning

benchmark_VAE vs PyTorch-VAE Awesome-VAEs vs PyTorch-VAE benchmark_VAE vs scvi-tools Awesome-VAEs vs awesome-datascience benchmark_VAE vs fastero Awesome-VAEs vs awesome-self-supervised-speech-representation-learning benchmark_VAE vs disentangling-vae Awesome-VAEs vs SimCLR benchmark_VAE vs nflows Awesome-VAEs vs disentangling-vae benchmark_VAE vs cloud_benchmarker Awesome-VAEs vs stanford-cs-229-machine-learning