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Statistical consistency in phylogenetics has traditionally referred to the accuracy of estimating phylogenetic parameters for a fixed number of species as we increase the number of characters. However, as sequences are often of fixed length…

Populations and Evolution · Quantitative Biology 2010-04-09 Olivier Gascuel , Mike Steel

Mixture model-based frameworks are very popular for statistical inference in clustering. While convenient for producing probabilistic estimates of cluster assignments and uncertainty, they are prone to misspecification, which can lead to…

Statistics Theory · Mathematics 2026-05-15 Yu Zheng , Leo L. Duan , Arkaprava Roy

Weak gravitational lensing surveys are rapidly becoming important tools to probe directly the mass density fluctuations in the universe and its background dynamics. Earlier studies have shown that it is possible to model the statistics of…

Astrophysics · Physics 2009-11-07 Patrick Valageas , Andrew J. Barber , Dipak Munshi

Statistical inference for exponential-family models of random graphs with dependent edges is challenging. We stress the importance of additional structure and show that additional structure facilitates statistical inference. A simple…

Statistics Theory · Mathematics 2020-03-13 Michael Schweinberger , Jonathan Stewart

Flux compactification of string theory generates an ensemble with a large number of vacua called the landscape. By using the statistics of various properties of low-energy effective theories in the string landscape, one can therefore hope…

High Energy Physics - Phenomenology · Physics 2015-01-07 Andreas P. Braun , Taizan Watari

Species trees represent the historical divergences of populations or species, while gene trees trace the ancestry of individual gene copies sampled within those populations. In cases involving rapid speciation, gene trees with topologies…

Populations and Evolution · Quantitative Biology 2015-08-28 James H. Degnan , John A. Rhodes

Phylogenetics uses alignments of molecular sequence data to learn about evolutionary trees relating species. Along branches, sequence evolution is modelled using a continuous-time Markov process characterised by an instantaneous rate…

Evolutionary models for populations of constant size are frequently studied using the Moran model, the Wright-Fisher model, or their diffusion limits. When evolution is neutral, a random genealogy given through Kingman's coalescent is used…

Populations and Evolution · Quantitative Biology 2012-07-31 Peter Pfaffelhuber , Benedikt Vogt

The spatial structure of an evolving population affects which mutations become fixed. Some structures amplify selection, increasing the likelihood that beneficial mutations become fixed while deleterious mutations do not. Other structures…

Phylogenetic trait evolution models allow for the estimation of evolutionary correlations between a set of traits observed in a sample of related organisms. By directly modeling the evolution of the traits along an estimable phylogenetic…

We propose a class of structured diffusion models, in which the prior distribution is chosen as a mixture of Gaussians, rather than a standard Gaussian distribution. The specific mixed Gaussian distribution, as prior, can be chosen to…

Machine Learning · Computer Science 2024-10-28 Nanshan Jia , Tingyu Zhu , Haoyu Liu , Zeyu Zheng

The spectral density of random graphs with topological constraints is analysed using the replica method. We consider graph ensembles featuring generalised degree-degree correlations, as well as those with a community structure. In each case…

Disordered Systems and Neural Networks · Physics 2011-04-08 Tim Rogers , Conrad Pérez Vicente , Koujin Takeda , Isaac Pérez Castillo

A graphical model is a statistical model that is associated to a graph whose nodes correspond to variables of interest. The edges of the graph reflect allowed conditional dependencies among the variables. Graphical models admit…

Methodology · Statistics 2016-06-09 Mathias Drton , Marloes H. Maathuis

Predicting stable and metastable structures is central to molecular and materials discovery, but remains limited by the cost of searching high-dimensional energy landscapes. Deep generative models offer efficient structure sampling, yet…

Artificial Intelligence · Computer Science 2026-05-26 Yifang Qin , Yu Shi , Junfu Tan , Chang Liu , Ming Zhang , Ziheng Lu

We pursue the analysis of nesting statistics in the $O(n)$ loop model on random maps, initiated for maps with the topology of disks and cylinders in math-ph/1605.02239, here for arbitrary topologies. For this purpose we rely on the…

Mathematical Physics · Physics 2023-06-30 Gaëtan Borot , Elba Garcia-Failde

Some recent studies have suggested using GANs for numeric data generation such as to generate data for completing the imbalanced numeric data. Considering the significant difference between the dimensions of the numeric data and images, as…

Machine Learning · Computer Science 2020-05-11 Wei Wang , Chuang Wang , Tao Cui , Yue Li

Tools that effectively analyze and compare sequences are of great importance in various areas of applied computational research, especially in the framework of molecular biology. In the present paper, we introduce simple geometric criteria…

Quantitative Methods · Quantitative Biology 2013-08-14 Boris Brimkov , Valentin E. Brimkov

In order to study the statistics of the objects with hierarchical merging, we propose the skeleton tree formalism, which can analytically distinguish the episodic merging and the continuous accretion in the mass growth processes. The…

Astrophysics · Physics 2009-10-31 Hitoshi Hanami

The topic of this letter is structure formation with topological defects. We first present a partially new, fully local and gauge invariant system of perturbation equations to treat microwave background and dark matter fluctuations induced…

Astrophysics · Physics 2010-11-01 Ruth Durrer , Zhi-hong Zhou

Learning a categorical distribution comes with its own set of challenges. A successful approach taken by state-of-the-art works is to cast the problem in a continuous domain to take advantage of the impressive performance of the generative…

Machine Learning · Computer Science 2023-03-09 Florence Regol , Mark Coates