disentangling-vae
memorization
disentangling-vae | memorization | |
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1 | 1 | |
766 | 5 | |
- | - | |
0.0 | 10.0 | |
over 1 year ago | over 2 years ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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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
memorization
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[D] DALL·E to be made available as API, OpenAI to give users full ownership rights to generated images
Codex is not technically copy pasting; it is generating a new output that is (almost) exactly the same, or indistinguishable on the eyes of a human, to the input. Sounds like semantics, but there is no actual copying. You already have music generating algorithms that can also generate short samples that are indistinguishable to the inputs (memorisation). Dall-E 2 is not there yet, but we are close to prompting "Original Mona Lisa painting" and be given back the original Mona Lisa painting with striking similarities. There are already several generative models of images that can mostly memorise inputs used to train it (quick example found using google: https://github.com/alan-turing-institute/memorization).
What are some alternatives?
Efficient-VDVAE - Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"
hydra-zen - Create powerful Hydra applications without the yaml files and boilerplate code.
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
scvi-tools - Deep probabilistic analysis of single-cell and spatial omics data
wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
classification - Classification of the MNIST dataset using various Deep Learning techniques
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
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.