Denoiser_Encoder-With-DNcnn
disentangling-vae
Denoiser_Encoder-With-DNcnn | disentangling-vae | |
---|---|---|
1 | 1 | |
1 | 766 | |
- | - | |
10.0 | 0.0 | |
almost 2 years ago | over 1 year ago | |
Python | Python | |
- | GNU General Public License v3.0 or later |
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.
Denoiser_Encoder-With-DNcnn
-
DNcnn: Residual Learning of Deep CNN for Image Denoising.
project git: https://github.com/AmzadHossainrafis/Denoiser_Encoder-With-DNcnn
disentangling-vae
-
[P] Python library for Variational Autoencoder benchmarking
There is a good repo of different beta-vae models here: https://github.com/YannDubs/disentangling-vae
What are some alternatives?
Efficient-VDVAE - Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
scvi-tools - Deep probabilistic analysis of single-cell and spatial omics data
classification - Classification of the MNIST dataset using various Deep Learning techniques
benchmark_VAE - Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
CelebAMask-HQ - A large-scale face dataset for face parsing, recognition, generation and editing.
minimal_VAE_on_Mario - A minimal VAE trained on Super Mario Bros levels.
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
pytask - pytask is a workflow management system that facilitates reproducible data analyses.
precision-recall-distributions - Assessing Generative Models via Precision and Recall (official repository)
memorization - Code for "On Memorization in Probabilistic Deep Generative Models"