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.

https://github.com/google-research/e3x

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
    Links to: arxiv.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (17.1%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.

Basic Info
Statistics
  • Stars: 108
  • Watchers: 7
  • Forks: 7
  • Open Issues: 0
  • Releases: 3
Created almost 3 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog Contributing License Authors

README.md

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E3x: E(3)-Equivariant Deep Learning Made Easy

Autopublish Workflow PyPI version Documentation Status

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

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

All Time
  • Total Commits: 24
  • Total Committers: 2
  • Avg Commits per committer: 12.0
  • Development Distribution Score (DDS): 0.125
Past Year
  • Commits: 3
  • Committers: 1
  • Avg Commits per committer: 3.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email 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
  • 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.

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 3,221 Last month
Rankings
Dependent packages count: 10.0%
Average: 38.1%
Dependent repos count: 66.1%
Maintainers (1)
Last synced: 7 months ago

Dependencies

pyproject.toml pypi
  • absl-py *
  • etils [epath]
  • flax *
  • jax *
  • jaxtyping *
  • more_itertools *
  • numpy *
  • sympy *
.github/workflows/pytest_and_autopublish.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • etils-actions/pypi-auto-publish v1 composite