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Phylogenetic networks provide a means of describing the evolutionary history of sets of species believed to have undergone hybridization or gene flow during their evolution. The mutation process for a set of such species can be modeled as a…

Populations and Evolution · Quantitative Biology 2022-11-23 Travis Barton , Elizabeth Gross , Colby Long , Joseph Rusinko

We introduce the zip tree, a form of randomized binary search tree that integrates previous ideas into one practical, performant, and pleasant-to-implement package. A zip tree is a binary search tree in which each node has a numeric rank…

Data Structures and Algorithms · Computer Science 2022-02-23 Robert E. Tarjan , Caleb C. Levy , Stephen Timmel

Phylogenetic networks are a special type of graph which generalize phylogenetic trees and that are used to model non-treelike evolutionary processes such as recombination and hybridization. In this paper, we consider {\em unrooted}…

Combinatorics · Mathematics 2025-05-21 Katharina T. Huber , Simone Linz , Vincent Moulton

Combining a set of phylogenetic trees into a single phylogenetic network that explains all of them is a fundamental challenge in evolutionary studies. Existing methods are computationally expensive and can either handle only small numbers…

Populations and Evolution · Quantitative Biology 2023-04-07 Giulia Bernardini , Leo van Iersel , Esther Julien , Leen Stougie

Tree search algorithms, such as branch-and-bound, are the most widely used tools for solving combinatorial and nonconvex problems. For example, they are the foremost method for solving (mixed) integer programs and constraint satisfaction…

Artificial Intelligence · Computer Science 2018-05-18 Maria-Florina Balcan , Travis Dick , Tuomas Sandholm , Ellen Vitercik

We present a simple 4-approximation algorithm for computing a maximum agreement forest of multiple unrooted binary trees. This algorithm applies LP rounding to an extension of a recent ILP formulation of the maximum agreement forest problem…

Data Structures and Algorithms · Computer Science 2024-09-16 Jordan Dempsey , Leo van Iersel , Mark Jones , Norbert Zeh

We use machine learning to classify examples of braids (or flat braids) as trivial or non-trivial. Our ML takes form of supervised learning using neural networks (multilayer perceptrons). When they achieve good results in classification, we…

Geometric Topology · Mathematics 2023-07-25 Alexei Lisitsa , Mateo Salles , Alexei Vernitski

Given two binary trees on $N$ labeled leaves, the quartet distance between the trees is the number of disagreeing quartets. By permuting the leaves at random, the expected quartets distance between the two trees is…

Combinatorics · Mathematics 2021-01-01 Benny Chor , Péter L. Erdős , Yonatan Komornik

The problem of pattern selection arises when the evolution equations have many solutions, whereas observed patterns constitute a much more restricted set. An approach is advanced for treating the problem of pattern selection by defining the…

Condensed Matter · Physics 2009-11-07 V. I. Yukalov

Phylogenetic networks are leaf-labelled directed acyclic graphs that are used to describe non-treelike evolutionary histories and are thus a generalization of phylogenetic trees. The hybridization number of a phylogenetic network is the sum…

Data Structures and Algorithms · Computer Science 2016-06-01 Leo van Iersel , Steven Kelk , Nela Lekić , Chris Whidden , Norbert Zeh

We are concerned with catalyst-assisted probabilistic entanglement transformations. A necessary and sufficient condition is presented under which there exist partial catalysts that can increase the maximal transforming probability of a…

Quantum Physics · Physics 2016-11-17 Yuan Feng , Runyao Duan , Mingsheng Ying

Clustering is a widely used unsupervised learning method for finding structure in the data. However, the resulting clusters are typically presented without any guarantees on their robustness; slightly changing the used data sample or…

Machine Learning · Statistics 2017-01-02 Andreas Henelius , Kai Puolamäki , Henrik Boström , Panagiotis Papapetrou

A common approach to aggregate classification estimates in an ensemble of decision trees is to either use voting or to average the probabilities for each class. The latter takes uncertainty into account, but not the reliability of the…

Machine Learning · Computer Science 2022-08-17 Florian Busch , Moritz Kulessa , Eneldo Loza Mencía , Hendrik Blockeel

There are few, if any, algorithms in statistical phylogenetics which are used more heavily than Felsenstein's 1973 pruning method for computing the likelihood of a tree. We present LvD, (Likelihood via Decomposition), an alternative to…

Populations and Evolution · Quantitative Biology 2026-01-28 David Bryant , Celine Scornavacca , David Swofford

An evolutionary tree (phylogenetic tree) is a binary, rooted, unordered tree that models the evolutionary history of currently living species in which leaves are labeled by species. In this paper, we investigate the problem of finding the…

Populations and Evolution · Quantitative Biology 2013-04-02 Soheil Jahangiri Tazehkand , Seyed Naser Hashemi , Hadi Poormohammadi

Probabilistic inference algorithms for finding the most probable explanation, the maximum aposteriori hypothesis, and the maximum expected utility and for updating belief are reformulated as an elimination--type algorithm called bucket…

Artificial Intelligence · Computer Science 2013-02-18 Rina Dechter

This paper develops likelihood-based methods for estimation, inference, model selection, and forecasting of continuous-time integer-valued trawl processes. The full likelihood of integer-valued trawl processes is, in general, highly…

Methodology · Statistics 2023-02-24 Mikkel Bennedsen , Asger Lunde , Neil Shephard , Almut E. D. Veraart

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. On the other hand, such hierarchical…

Machine Learning · Computer Science 2022-01-25 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

Achieving invariance to nuisance transformations is a fundamental challenge in the construction of robust and reliable vision systems. Existing approaches to invariance scale exponentially with the dimension of the family of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-11 Sam Buchanan , Jingkai Yan , Ellie Haber , John Wright

We study Thurston equivalence classes of quadratic post-critically finite branched coverings. For these maps, we introduce and study invariant spanning trees. We give a computational procedure for searching for invariant spanning trees.…

Dynamical Systems · Mathematics 2021-01-08 Anastasia Shepelevtseva , Vladlen Timorin
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