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相关论文: Likelihood-free inference of phylogenetic tree pos…

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Likelihood-free methods are an essential tool for performing inference for implicit models which can be simulated from, but for which the corresponding likelihood is intractable. However, common likelihood-free methods do not scale well to…

统计方法学 · 统计学 2022-07-15 Christopher Drovandi , David J Nott , David T Frazier

The multispecies coalescent process models the genealogical relationships of genes sampled from several species, enabling useful predictions about phenomena such as the discordance between the gene tree and the species phylogeny due to…

种群与进化 · 定量生物学 2020-12-11 Jakub Truszkowski , Celine Scornavacca , Fabio Pardi

Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available information are typically lists of homologous (lexical,…

物理与社会 · 物理学 2015-05-27 Simone Pompei , Vittorio Loreto , Francesca Tria

We present an alternative method for calculating likelihoods in molecular phylogenetics. Our method is based on partial likelihood tensors, which are generalizations of partial likelihood vectors, as used in Felsenstein's approach.…

定量方法 · 定量生物学 2008-07-23 J. G. Sumner , M. A. Charleston

Phylogenetic trees elucidate evolutionary relationships among species, but phylogenetic inference remains challenging due to the complexity of combining continuous (branch lengths) and discrete parameters (tree topology). Traditional Markov…

种群与进化 · 定量生物学 2024-12-30 ChenRui Duan , Zelin Zang , Siyuan Li , Yongjie Xu , Stan Z. Li

Phylogenetic inference, grounded in molecular evolution models, is essential for understanding the evolutionary relationships in biological data. Accounting for the uncertainty of phylogenetic tree variables, which include tree topologies…

机器学习 · 计算机科学 2023-12-04 Takahiro Mimori , Michiaki Hamada

We present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary networks: a summary network for data compression and an…

机器学习 · 计算机科学 2024-12-30 Jice Zeng , Yuanzhe Wang , Alexandre M. Tartakovsky , David Barajas-Solano

Several rapid parameter estimation methods have recently been advanced to deal with the computational challenges of the problem of Bayesian inference of the properties of compact binary sources detected in the upcoming science runs of the…

广义相对论与量子宇宙学 · 物理学 2023-12-05 Lalit Pathak , Amit Reza , Anand S. Sengupta

We describe an "embarrassingly parallel" method for Bayesian phylogenetic inference, annealed Sequential Monte Carlo, based on recent advances in the Sequential Monte Carlo literature such as adaptive determination of annealing parameters.…

种群与进化 · 定量生物学 2019-03-15 Liangliang Wang , Shijia Wang , Alexandre Bouchard-Côté

We analyse a maximum-likelihood approach for combining phylogenetic trees into a larger `supertree'. This is based on a simple exponential model of phylogenetic error, which ensures that ML supertrees have a simple combinatorial description…

种群与进化 · 定量生物学 2007-08-17 Mike Steel , Allen Rodrigo

Given i.i.d. data from an unknown distribution, we consider the problem of predicting future items. An adaptive way to estimate the probability density is to recursively subdivide the domain to an appropriate data-dependent granularity. A…

概率论 · 数学 2009-12-30 Marcus Hutter

Least squares estimation of phylogenies is an established family of methods with good statistical properties. State-of-the-art least squares phylogenetic estimation proceeds by first estimating a distance matrix, which is then used to…

种群与进化 · 定量生物学 2024-06-24 Peter B. Chi , Volodymyr M. Minin

Most of major algorithms for phylogenetic tree reconstruction assume that sequences in the analyzed set either do not have any offspring, or that parent sequences can maximally mutate into just two descendants. The graph resulting from such…

种群与进化 · 定量生物学 2013-10-09 Piotr Plonski , Jan P. Radomski

Background: Continuous traits evolution of a group of taxa that are correlated through a phylogenetic tree is commonly modelled using parametric stochastic differential equations to represent deterministic change of trait through time,…

种群与进化 · 定量生物学 2026-04-03 Bayu Brahmantio , Krzysztof Bartoszek , Etka Yapar

The aim of this review is to present and analyze the probabilistic models of mathematical phylogenetics which have been intensively used in recent years in biology as the cornerstone of attempts to infer and reconstruct the ancestral…

种群与进化 · 定量生物学 2020-01-08 Peter D Jarvis , Jeremy G Sumner

Phylogenetic network is an evolutionary model that uses a rooted directed acyclic graph (instead of a tree) to model an evolutionary history of species in which reticulate events (e.g., hybrid speciation or horizontal gene transfer)…

种群与进化 · 定量生物学 2023-12-01 Yufeng Wu , Louxin Zhang

Gaussian process regression can flexibly represent the posterior distribution of an interest parameter given sufficient information on the likelihood. However, in some cases, we have little knowledge regarding the probability model. For…

机器学习 · 计算机科学 2025-07-22 Yuta Shikuri

It is common in phylogenetics to have some, perhaps partial, information about the overall evolutionary tree of a group of organisms and wish to find an evolutionary tree of a specific gene for those organisms. There may not be enough…

种群与进化 · 定量生物学 2018-01-09 Vu Dinh , Lam Si Tung Ho , Marc A. Suchard , Frederick A. Matsen

Accurate simulation of complex physical systems enables the development, testing, and certification of control strategies before they are deployed into the real systems. As simulators become more advanced, the analytical tractability of the…

机器人学 · 计算机科学 2020-05-27 Lucas Barcelos , Rafael Oliveira , Rafael Possas , Lionel Ott , Fabio Ramos

Bayesian inference without the likelihood evaluation, or likelihood-free inference, has been a key research topic in simulation studies for gaining quantitatively validated simulation models on real-world datasets. As the likelihood…

统计方法学 · 统计学 2022-11-07 Dongjun Kim , Kyungwoo Song , YoonYeong Kim , Yongjin Shin , Wanmo Kang , Il-Chul Moon , Weonyoung Joo