benchmark_VAE
cloud_benchmarker
benchmark_VAE | cloud_benchmarker | |
---|---|---|
4 | 4 | |
1,695 | 32 | |
- | - | |
6.1 | 6.9 | |
about 1 month ago | 8 months ago | |
Python | Python | |
Apache License 2.0 | - |
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.
benchmark_VAE
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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
cloud_benchmarker
- Show HN: Cloud Benchmarker: See how fast your cloud instances are for real
- Cloud Benchmarker: See how fast your cloud instances are for real!
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Cloud Benchmarker: See how fast your cloud instances are for real! (Python Open-Source)
GitHub Repo: https://github.com/Dicklesworthstone/cloud_benchmarker
- Show HN: Cloud Benchmarker: See how fast your cloud instances are
What are some alternatives?
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
pytest-benchmark - py.test fixture for benchmarking code
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
pyperf - Toolkit to run Python benchmarks
scvi-tools - Deep probabilistic analysis of single-cell and spatial omics data
Merlion - Merlion: A Machine Learning Framework for Time Series Intelligence
fastero - Python timeit CLI for the 21st century! colored output, multi-line input with syntax highlighting and autocompletion and much more!
disentangling-vae - Experiments for understanding disentanglement in VAE latent representations
locust - Write scalable load tests in plain Python 🚗💨
nflows - Normalizing flows in PyTorch
CARLA - CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms