Evaluation Metrics for Protein Structure Generation
Abstract
Generative models have become increasingly popular for sampling novel proteins. To compare and evaluate these models, we need metrics that can assess the quality of the generated structures. We propose a set of standardized metrics for benchmarking protein generation. We experimentally show that these metrics can measure differences between proteins on a distributional level, as well as quantify the novelty, diversity and designability of the generated proteins.
Cite
Text
Southern et al. "Evaluation Metrics for Protein Structure Generation." ICML 2023 Workshops: DeployableGenerativeAI, 2023.Markdown
[Southern et al. "Evaluation Metrics for Protein Structure Generation." ICML 2023 Workshops: DeployableGenerativeAI, 2023.](https://mlanthology.org/icmlw/2023/southern2023icmlw-evaluation/)BibTeX
@inproceedings{southern2023icmlw-evaluation,
title = {{Evaluation Metrics for Protein Structure Generation}},
author = {Southern, Joshua and Schneuing, Arne and Bronstein, Michael M. and Correia, Bruno},
booktitle = {ICML 2023 Workshops: DeployableGenerativeAI},
year = {2023},
url = {https://mlanthology.org/icmlw/2023/southern2023icmlw-evaluation/}
}