activity
20032023
most citedConvexity in Tree Spaces

42 citations · 208 across the 51 of their papers we have counts for

collaborators

52 papers

cs.DM2023

Tropical neural networks and its applications to classifying phylogenetic trees

Ruriko Yoshida, Georgios Aliatimis, Keiji Miura

Deep neural networks show great success when input vectors are in an Euclidean space. However, those classical neural networks show a poor performance when inputs are phylogenetic…

q-bio.PE2023

Imputing phylogenetic trees using tropical polytopes over the space of phylogenetic trees

Ruriko Yoshida

When we apply comparative phylogenetic analyses to genome data, it is a well-known problem and challenge that some of given species (or taxa) often have missing genes. In such a ca…

math.CO2023

Tropical Logistic Regression Model on Space of Phylogenetic Trees

Georgios Aliatimis, Ruriko Yoshida, Burak Boyaci +1

Classification of gene trees is an important task both in the analysis of multi-locus phylogenetic data, and assessment of the convergence of Markov Chain Monte Carlo (MCMC) analys…

math.CO2023

Maximum Inscribed and Minimum Enclosing Tropical Balls of Tropical Polytopes and Applications to Volume Estimation and Uniform Sampling

David Barnhill, Ruriko Yoshida, Keiji Miura

We consider a minimum enclosing and maximum inscribed tropical balls for any given tropical polytope over the tropical projective torus in terms of the tropical metric with the max…

math.CO2022★ 6 cited

Hit and Run Sampling from Tropically Convex Sets

Ruriko Yoshida, Keiji Miura, David Barnhill

In this paper we propose Hit and Run (HAR) sampling from a tropically convex set. The key ingredient of HAR sampling from a tropically convex set is sampling uniformly from a tropi…

q-bio.PE2022★ 1 cited

Tropical Density Estimation of Phylogenetic Trees

Ruriko Yoshida, David Barnhill, Keiji Miura +1

Much evidence from biological theory and empirical data indicates that, gene tree, phylogenetic trees reconstructed from different genes (loci), do not have to have exactly the sam…