停车树与 nestohedra 的toric g向量
机器学习
2025-11-10 v1 人工智能
生物大分子
摘要
我们以非负整数线性组合的方式表达简单多面体的toric g向量条目。我们证明，associahedron的toric g向量是123-避免停车函数的上升统计量。类似地，cyclohedron的toric g向量对应于123-避免函数。我们证明，permutahedron的toric g向量记录了代表123-避免停车函数的停车树的上升统计量。我们指出了这种方法如何推广至所有和弦nestohedra。
引用
@article{arxiv.2511.04814,
title = {A Standardized Benchmark for Multilabel Antimicrobial Peptide Classification},
author = {Sebastian Ojeda and Rafael Velasquez and Nicolás Aparicio and Juanita Puentes and Paula Cárdenas and Nicolás Andrade and Gabriel González and Sergio Rincón and Carolina Muñoz-Camargo and Pablo Arbeláez},
journal= {arXiv preprint arXiv:2511.04814},
year = {2025}
}
备注
39th Conference on Neural Information Processing Systems (NeurIPS 2025). Camera-ready version. Code: https://github.com/BCV-Uniandes/ESCAPE. Dataset DOI: https://doi.org/10.7910/DVN/C69MCD