vae-anomaly-detector
Experiments on unsupervised anomaly detection using variational autoencoder. The variational autoencoder is implemented in Pytorch. (by JGuymont)
precision-recall-distributions
Assessing Generative Models via Precision and Recall (official repository) (by msmsajjadi)
| vae-anomaly-detector | precision-recall-distributions | |
|---|---|---|
| 1 | 1 | |
| 67 | 100 | |
| - | - | |
| 0.0 | 0.0 | |
| 11 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | 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.
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.
vae-anomaly-detector
Posts with mentions or reviews of vae-anomaly-detector.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Are there VAEs specific to 1d inputs instead of images?
Recently ran into this same issue. Here is a repo for a 1D VAE that I found to be clear and well implemented. Python code for the VAE here.
precision-recall-distributions
Posts with mentions or reviews of precision-recall-distributions.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-02-15.
-
[R] What are some up-to-date references to the evaluation of model fit across various types of generative models (GANs, flows, VAEs, diffusion, etc.)?
Code for https://arxiv.org/abs/1806.00035 found: https://github.com/msmsajjadi/precision-recall-distributions
What are some alternatives?
When comparing vae-anomaly-detector and precision-recall-distributions you can also consider the following projects:
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
ODMO - [ACMMM 2022] Official PyTorch Implementation of "Action-conditioned On-demand Motion Generation". ACM MultiMedia 2022.
the-gan-zoo - A list of all named GANs!
fcdd - Repository for the Explainable Deep One-Class Classification paper
generative-evaluation-prdc - Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
disentangling-vae - Experiments for understanding disentanglement in VAE latent representations
vae-anomaly-detector vs PyTorch-VAE
precision-recall-distributions vs pytorch-CycleGAN-and-pix2pix
vae-anomaly-detector vs ODMO
precision-recall-distributions vs the-gan-zoo
vae-anomaly-detector vs fcdd
precision-recall-distributions vs generative-evaluation-prdc
precision-recall-distributions vs disentangling-vae