memorization
Code for "On Memorization in Probabilistic Deep Generative Models" (by alan-turing-institute)
benchmark_VAE
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022) (by clementchadebec)
memorization | benchmark_VAE | |
---|---|---|
1 | 4 | |
5 | 1,691 | |
- | - | |
10.0 | 6.1 | |
over 2 years ago | about 1 month 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.
memorization
Posts with mentions or reviews of memorization.
We have used some of these posts to build our list of alternatives
and similar projects.
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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).
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.
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Researchers From INRIA France Propose ‘Pythae’: An Open-Source Python Library Unifying Common And State-of-the-Art Generative AutoEncoder (GAE) Implementations
Continue reading | Checkout the paper, github
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[P] Pythae - Unifying generative autoencoder implementations in Python
Code for https://arxiv.org/abs/2206.08309 found: https://github.com/clementchadebec/benchmark_VAE
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[P] Python library for Variational Autoencoder benchmarking
Github link: https://github.com/clementchadebec/benchmark_VAE
- Python library for Variational Autoencoder Benchmarking
What are some alternatives?
When comparing memorization and benchmark_VAE you can also consider the following projects:
hydra-zen - Create powerful Hydra applications without the yaml files and boilerplate code.
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.