atomicarchitects / equiformer_v2
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Why this job: works in the areas we cover, but does not say which job it does
What it does
This repository contains the official PyTorch implementation of the work "EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations" (ICLR 2024). We provide the code for training the base model setting on the OC20 S2EF-2M and S2EF-All+MD datasets.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Inactive
- Last commit 7 months ago
- Stars
- 354
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 33% closed
- 18 still open
- Pull requests
- 0 merged
- 2 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
- Shell <1%
Topics
- catalyst-design
- computational-chemistry
- computational-physics
- deep-learning
- drug-discovery
- equivariant-graph-neural-network
- equivariant-neural-networks
- force-fields
- interatomic-potentials
- machine-learning
- molecular-dynamics
- pytorch
Project record
- JobOther AI tools
- StatusListed
- Commits18
- Forks50
- Watching6
- Stars in 28 days+1
- CreatedJun 21, 2023
- First seen by usNov 7, 2026
- CheckedNov 8, 2026