2024/04/29 by Hanh Vo, Vo, Hanh, Puttipong Pongtanapaisan +2
Computer Science · #Advanced Graph Neural Networks #FOS: Computer and information sciences #FOS: Mathematics #Geometric Topology (math.GT) #Machine Learning (cs.LG) #Machine Learning and Algorithms #Rough Sets and Fuzzy Logic
paper · pdf · doi:10.48550/arxiv.2405.05272
openalex publication_date 2024/04/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper employs various computational techniques to determine the bridge numbers of both classical and virtual knots. For classical knots, there is no ambiguity of what the bridge number means. For virtual knots, there are multiple natural definitions of bridge number, and we demonstrate that the difference can be arbitrarily far apart. We then acquired two datasets, one for classical and one for virtual knots, each comprising over one million labeled data points. With the data, we conduct experiments to evaluate the effectiveness of common machine learning models in classifying knots based on their bridge numbers.