Awesome-VAEs VS awesome-self-supervised-speech-representation-learning

Compare Awesome-VAEs vs awesome-self-supervised-speech-representation-learning and see what are their differences.

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Awesome-VAEs awesome-self-supervised-speech-representation-learning
1 1
755 4
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0.0 0.0
almost 3 years ago over 2 years ago
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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.

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

awesome-self-supervised-speech-representation-learning

Posts with mentions or reviews of awesome-self-supervised-speech-representation-learning. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Awesome-VAEs and awesome-self-supervised-speech-representation-learning you can also consider the following projects:

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

Awesome-pytorch-list - A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

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

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

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

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

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