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The matrices of spanning rooted forests are studied as a tool for analysing the structure of networks and measuring their properties. The problems of revealing the basic bicomponents, measuring vertex proximity, and ranking from preference…

Combinatorics · Mathematics 2013-05-29 Pavel Chebotarev , Rafig Agaev

It is possible to formulate 2d field theory on the ultrametric space with the free correlators identical to 2d correlators and the same potential. Such model should carry some features of original model for scale invariant theories. For the…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. B. Saakian

Bayesian phylogenetics is vital for understanding evolutionary dynamics, and requires accurate and efficient approximation of posterior distributions over trees. In this work, we develop a variational Bayesian approach for ultrametric…

Machine Learning · Statistics 2026-02-16 Evan Sidrow , Alexandre Bouchard-Côté , Lloyd T. Elliott

The Robinson-Foulds (RF) distance is by far the most widely used measure of dissimilarity between trees. Although the distribution of these distances has been investigated for twenty years, an algorithm that is explicitly polynomial time…

Populations and Evolution · Quantitative Biology 2008-10-07 David Bryant , Mike Steel

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 same tree topologies. Such incongruence between gene trees…

Populations and Evolution · Quantitative Biology 2023-07-13 Ruriko Yoshida , David Barnhill , Keiji Miura , Daniel Howe

A random forest prediction can be computed by the scalar product of the labels of the training examples and a set of weights that are determined by the leafs of the forest into which the test object falls; each prediction can hence be…

Machine Learning · Computer Science 2023-11-27 Henrik Boström

This paper presents two approaches to quantifying and visualizing variation in datasets of trees. The first approach localizes subtrees in which significant population differences are found through hypothesis testing and sparse classifiers…

We propose a principled method for autoencoding with random forests. Our strategy builds on foundational results from nonparametric statistics and spectral graph theory to learn a low-dimensional embedding of the model that optimally…

Machine Learning · Statistics 2026-01-16 Binh Duc Vu , Jan Kapar , Marvin Wright , David S. Watson

The present lecture notes give an introduction to works of Garc\'{i}a Barroso, Gonz\'alez P\'erez, Ruggiero and the author. The starting point of those works is a theorem of P\l oski, stating that one defines an ultrametric on the set of…

Algebraic Geometry · Mathematics 2020-07-14 Patrick Popescu-Pampu

There are several interrelated notions of discrete curvature on graphs. Many approaches utilize the optimal transportation metric on its probability simplex or the distance matrix of the graph. In this survey article, we compute formulas…

Combinatorics · Mathematics 2025-11-04 Sawyer Jack Robertson

Phylogenetic trees are the fundamental mathematical representation of evolutionary processes in biology. They are also objects of interest in pure mathematics, such as algebraic geometry and combinatorics, due to their discrete geometry.…

Metric Geometry · Mathematics 2022-07-01 Anthea Monod , Bo Lin , Ruriko Yoshida , Qiwen Kang

We introduce a novel interpretable tree based algorithm for prediction in a regression setting. Our motivation is to estimate the unknown regression function from a functional decomposition perspective in which the functional components…

Machine Learning · Statistics 2023-08-04 Munir Hiabu , Enno Mammen , Joseph T. Meyer

We consider fixed-point equations for probability measures charging measured compact metric spaces that naturally yield continuum random trees. On the one hand, we study the existence/uniqueness of the fixed-points and the convergence of…

Probability · Mathematics 2021-05-05 Nicolas Broutin , Henning Sulzbach

Ensemble methods such as random forests have transformed the landscape of supervised learning, offering highly accurate prediction through the aggregation of multiple weak learners. However, despite their effectiveness, these methods often…

Machine Learning · Computer Science 2026-05-29 Massimo Aria , Agostino Gnasso , Carmela Iorio , Marjolein Fokkema

In this paper, we consider the problem of reconstructing trees from traces in the tree edit distance model. Previous work by Davies et al. (2019) analyzed special cases of reconstructing labeled trees. In this work, we significantly expand…

Computational Complexity · Computer Science 2022-01-14 Thomas Maranzatto

A non-local model describing the growth of a tree-like transportation network with given allocation rules is proposed. In this model we focus on tree like networks, and the network transports the very resource it needs to build itself. Some…

Adaptation and Self-Organizing Systems · Physics 2019-07-24 Olivier Bui , Xavier Leoncini

The basin of infinity of a polynomial map $f : {\bf C} \arrow {\bf C}$ carries a natural foliation and a flat metric with singularities, making it into a metrized Riemann surface $X(f)$. As $f$ diverges in the moduli space of polynomials,…

Dynamical Systems · Mathematics 2011-11-09 Laura G. DeMarco , Curtis T. McMullen

The wealth of data being gathered about humans and their surroundings drives new machine learning applications in various fields. Consequently, more and more often, classifiers are trained using not only numerical data but also complex data…

Machine Learning · Computer Science 2022-04-13 Maciej Piernik , Dariusz Brzezinski , Pawel Zawadzki

Merge trees are a type of topological descriptors that record the connectivity among the sublevel sets of scalar fields. They are among the most widely used topological tools in visualization. In this paper, we are interested in sketching a…

Computational Geometry · Computer Science 2021-06-01 Mingzhe Li , Sourabh Palande , Lin Yan , Bei Wang

It is shown that the rooted trees $T_X$ and $T_Y$ representing finite ultrametric spaces $X$ and $Y$ are isomorphic if and only if there exists a ball-preserving bijection $F:X\to Y$.

Metric Geometry · Mathematics 2013-02-26 E. Petrov
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