https://github.com/ml-jku/chem-xlstm
https://github.com/ml-jku/chem-xlstm
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/ml-jku/chem-xlstm
- Owner: ml-jku
- License: apache-2.0
- Created: 2024-11-05T14:11:14.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-02-21T09:55:33.000Z (3 months ago)
- Last Synced: 2025-02-21T10:29:26.992Z (3 months ago)
- Size: 81.7 MB
- Stars: 9
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Chem-xLSTM
This repository provides the code necessary to reproduce the experiments presented in the paper [Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences](https://arxiv.org/abs/2411.04165). The code is organized across the following repositories:
- [Chem-xLSTM](https://github.com/ml-jku/Chem-xLSTM/) (current repository)
- [DNA-xLSTM](https://github.com/ml-jku/DNA-xLSTM/)
- [Prot-xLSTM](https://github.com/ml-jku/Prot-xLSTM/)
## Chem-xLSTM
Chem-xLSTM codebase is currently under construction and will be released soon.
### Citation
```latex
@article{schmidinger2024bio-xlstm,
title={{Bio-xLSTM}: Generative modeling, representation and in-context learning of biological and chemical sequences},
author={Niklas Schmidinger and Lisa Schneckenreiter and Philipp Seidl and Johannes Schimunek and Pieter-Jan Hoedt and Johannes Brandstetter and Andreas Mayr and Sohvi Luukkonen and Sepp Hochreiter and Günter Klambauer},
journal={arXiv},
doi = {},
year={2024},
url={}
}
```