https://github.com/google-research/e3x
E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (17.1%) to scientific vocabulary
Repository
E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.
Basic Info
- Host: GitHub
- Owner: google-research
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://e3x.readthedocs.io/stable/
- Size: 99.8 MB
Statistics
- Stars: 108
- Watchers: 7
- Forks: 7
- Open Issues: 0
- Releases: 3
Metadata Files
README.md
E3x: E(3)-Equivariant Deep Learning Made Easy
E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.
The goal is to provide common neural network building blocks for E(3)-equivariant architectures to make the development of models operating on three-dimensional data (point clouds, polygon meshes, etc.) easier.
This is not an officially supported Google product.
Installation
The easiest way to install E3x is via the Python Package Index (PyPI). Simply run ```console
python -m pip install --upgrade e3x ``` and you should be good to go.
Alternatively, you can clone this repository, enter the directory and run: ```console
python -m pip install . ```
If you are a developer, you might want to also install the optional development dependencies by running ```console
python -m pip install .[dev] ``` instead.
Documentation
Documentation for E3x, including usage examples and tutorials can be found here. For a more detailed overview over the mathematical theory behind E3x, please refer to this paper.
Citing E3x
If you find E3x useful and use it in your work, please cite:
@article{unke2024e3x,
title={\texttt{E3x}: $\mathrm{E}(3)$-Equivariant Deep Learning Made Easy},
author={Unke, Oliver T. and Maennel, Hartmut},
journal={arXiv preprint arXiv:2401.07595},
year={2024}
}
Owner
- Name: Google Research
- Login: google-research
- Kind: organization
- Location: Earth
- Website: https://research.google
- Repositories: 226
- Profile: https://github.com/google-research
GitHub Events
Total
- Issues event: 4
- Watch event: 22
- Delete event: 3
- Issue comment event: 2
- Push event: 10
- Pull request event: 4
- Fork event: 1
- Create event: 3
Last Year
- Issues event: 4
- Watch event: 22
- Delete event: 3
- Issue comment event: 2
- Push event: 10
- Pull request event: 4
- Fork event: 1
- Create event: 3
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Oliver Unke | o****e@g****m | 21 |
| The e3x Authors | n****y@g****m | 3 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 8 months ago
All Time
- Total issues: 3
- Total pull requests: 22
- Average time to close issues: 10 days
- Average time to close pull requests: 3 days
- Total issue authors: 3
- Total pull request authors: 2
- Average comments per issue: 1.0
- Average comments per pull request: 0.09
- Merged pull requests: 10
- Bot issues: 0
- Bot pull requests: 21
Past Year
- Issues: 2
- Pull requests: 3
- Average time to close issues: 8 days
- Average time to close pull requests: about 4 hours
- Issue authors: 2
- Pull request authors: 1
- Average comments per issue: 1.0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 3
Top Authors
Issue Authors
- Chronum94 (1)
- curtischong (1)
- sirmarcel (1)
Pull Request Authors
- copybara-service[bot] (42)
- OUnke (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 3,221 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 3
- Total maintainers: 1
pypi.org: e3x
JAX-Library for building E(3)-equivariant deep learning architectures based on Flax.
- Documentation: https://e3x.readthedocs.io/
- License: Apache Software License
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Latest release: 1.0.2
published about 2 years ago
Rankings
Maintainers (1)
Dependencies
- absl-py *
- etils [epath]
- flax *
- jax *
- jaxtyping *
- more_itertools *
- numpy *
- sympy *
- actions/checkout v3 composite
- actions/setup-python v4 composite
- etils-actions/pypi-auto-publish v1 composite