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Bayesian phylogenetic inference is currently done via Markov chain Monte Carlo (MCMC) with simple proposal mechanisms. This hinders exploration efficiency and often requires long runs to deliver accurate posterior estimates. In this paper,…

Machine Learning · Statistics 2024-05-24 Cheng Zhang , Frederick A. Matsen

Neutral macroevolutionary models, such as the Yule model, give rise to a probability distribution on the set of discrete rooted binary trees over a given leaf set. Such models can provide a signal as to the approximate location of the root…

Populations and Evolution · Quantitative Biology 2012-03-28 Mike Steel

We introduce a class of maximum-entropy states that naturally includes within it all of the major continuous-time stochastic processes that have been applied to animal movement, including Brownian motion, Ornstein-Uhlenbeck motion,…

Statistical Mechanics · Physics 2015-03-11 Chris H. Fleming , Yigit Subasi , Justin M. Calabrese

Cubical complexes are metric spaces constructed by gluing together unit cubes in an analogous way to the construction of simplicial complexes. We construct Brownian motion on such spaces, define random walks, and prove that the transition…

Populations and Evolution · Quantitative Biology 2019-05-23 Tom M. W. Nye

We suggest a generalization of the Feynman path integral to an integral over random surfaces. The proposed action is proportional to the linear size of the random surfaces and is called gonihedric. The convergence and the properties of the…

High Energy Physics - Theory · Physics 2016-12-13 George Savvidy

We propose a metric space of coalescing pairs of paths on which we are able to prove (more or less) directly convergence of objects such as the persistence probability in the (one dimensional, nearest neighbor, symmetric) voter model or the…

Probability · Mathematics 2018-11-29 Luiz Renato Fontes

A theorem due to D. Bernstein states that Euler characteristic of a hypersurface defined by a polynomial f in (C\{0})^n is equal (upto a sign) to n! times volume of the Newton polyhedron of f. This result is related to algebaric torus…

Algebraic Geometry · Mathematics 2007-05-23 Kiumars Kaveh

The Bayesian method is noted to produce spuriously high posterior probabilities for phylogenetic trees in analysis of large datasets, but the precise reasons for this over-confidence are unknown. In general, the performance of Bayesian…

Statistics Theory · Mathematics 2018-10-15 Ziheng Yang , Tianqi Zhu

We demonstrate that the update of weight matrices in learning algorithms can be described in the framework of Dyson Brownian motion, thereby inheriting many features of random matrix theory. We relate the level of stochasticity to the ratio…

Disordered Systems and Neural Networks · Physics 2025-01-10 Gert Aarts , Biagio Lucini , Chanju Park

The toric variety of a matroid is projectively normal, and therefore it is Cohen-Macaulay. We provide a complete graph-theoretic classification when the toric variety of a graphic matroid is Gorenstein.

Combinatorics · Mathematics 2021-11-30 Takayuki Hibi , Michał Lasoń , Kazunori Matsuda , Mateusz Michałek , Martin Vodička

A general theory is provided delivering convergence of maximal cyclically monotone mappings containing the supports of coupling measures of sequences of pairs of possibly random probability measures on Euclidean space. The theory is based…

Statistics Theory · Mathematics 2022-08-05 Johan Segers

Bayesian inference for phylogenetics is a gold standard for computing distributions of phylogenies. It faces the challenging problem of. moving throughout the high-dimensional space of trees. However, hyperbolic space offers a low…

Populations and Evolution · Quantitative Biology 2023-07-19 Matthew Macaulay , Aaron E. Darling , Mathieu Fourment

We consider a special family of Gaussian hypergeometric functions whose entries are cubic and trivial characters over finite fields. The special values of these functions are known to give the Frobenius traces of families of Hessian…

Number Theory · Mathematics 2025-02-14 Ken Ono , Sudhir Pujahari , Hasan Saad , Neelam Saikia

We provide a complete description of possible covariance matrices consistent with a Gaussian latent tree model for any tree. We then present techniques for utilising these constraints to assess whether observed data is compatible with that…

Methodology · Statistics 2016-04-13 Nathaniel Shiers , Piotr Zwiernik , John A. D. Aston , Jim Q. Smith

We design a theoretic tree-based functional representation of a class of Feynman-Kac particle distributions, including an extension of the Wick product formula to interacting particle systems. These weak expansions rely on an original…

Probability · Mathematics 2016-08-16 Pierre Del Moral , Frédéric Patras , Sylvain Rubenthaler

For a model of molecular evolution to be useful for phylogenetic inference, the topology of evolutionary trees must be identifiable. That is, from a joint distribution the model predicts, it must be possible to recover the tree parameter.…

Populations and Evolution · Quantitative Biology 2011-11-09 Elizabeth S. Allman , John A. Rhodes

Real-world signals typically span across multiple dimensions, that is, they naturally reside on multi-way data structures referred to as tensors. In contrast to standard ``flat-view'' multivariate matrix models which are agnostic to data…

Signal Processing · Electrical Eng. & Systems 2019-12-04 Bruno Scalzo Dees , Anh-Huy Phan , Danilo P. Mandic

We show that the tropical projective Grassmannian of planes is homeomorphic to a closed subset of the analytic Grassmannian in Berkovich's sense by constructing a continuous section to the tropicalization map. Our main tool is an explicit…

Algebraic Geometry · Mathematics 2014-03-12 Maria Angelica Cueto , Mathias Haebich , Annette Werner

Survival models are used to analyze time-to-event data in a variety of disciplines. Proportional hazard models provide interpretable parameter estimates, but proportional hazards assumptions are not always appropriate. Non-parametric models…

Methodology · Statistics 2022-07-08 Richard D. Payne , Nilabja Guha , Bani K. Mallick

We present a novel prior for tree topology within Bayesian Additive Regression Trees (BART) models. This approach quantifies the hypothetical loss in information and the loss due to complexity associated with choosing the wrong tree…

Methodology · Statistics 2024-12-30 F. Serafini , F. Leisen , C. Villa , K. Wilson