Welcome to torchtree!#
Warning
The documentation corresponds to the current state of the main branch. There may be differences with the latest released version.
torchtree is a program designed for developing and inferring phylogenetic models. It is implemented in Python and uses PyTorch to leverage automatic differentiation. Inference algorithms include variational inference, Hamiltonian Monte Carlo, maximum a posteriori and Markov chain Monte Carlo.
For a comprehensive assessment of torchtree’s performance and use cases, please see our evaluation repository, torchtree-experiments, where torchtree was rigorously tested on various datasets and benchmarked for accuracy and speed.
Installation#
git clone https://github.com/4ment/torchtree
pip install torchtree/
pip install torchtree
Getting Started
How to cite#
Mathieu Fourment, Matthew Macaulay, Christiaan J Swanepoel, Xiang Ji, Marc A Suchard and Frederick A Matsen IV. torchtree: flexible phylogenetic model development and inference using PyTorch, 2024 arXiv:2406.18044
@misc{fourment2024torchtree,
title={torchtree: flexible phylogenetic model development and inference using {PyTorch}},
author={Mathieu Fourment and Matthew Macaulay and Christiaan J Swanepoel and Xiang Ji and Marc A Suchard and Frederick A Matsen IV},
year={2024},
eprint={2406.18044},
archivePrefix={arXiv},
primaryClass={q-bio.PE},
url={https://arxiv.org/abs/2406.18044}
}