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Transition path theory (TPT) for diffusion processes is a framework for analysing the transitions of multiscale ergodic diffusion processes between disjoint metastable subsets of state space. Most methods for applying TPT involve the…

Numerical Analysis · Mathematics 2021-03-31 Nada Cvetković , Tim Conrad , Han Cheng Lie

The formula for the probability of fixation of a new mutation is widely used in theoretical population genetics and molecular evolution. Here we derive a series of identities, inequalities and approximations for the exact probability of…

Populations and Evolution · Quantitative Biology 2015-03-10 David M. McCandlish , Charles L. Epstein , Joshua B. Plotkin

We consider the problem of inference for the states and parameters of a continuous-time multitype branching process from partially observed time series data. Exact inference for this class of models, typically using sequential Monte Carlo,…

Methodology · Statistics 2025-12-01 Angus Lewis , Antonio Parrella , John Maclean , Andrew J. Black

Many real-world machine learning tasks require outputs that satisfy hard constraints, such as physical conservation laws, structured dependencies in graphs, or column-level relationships in tabular data. Existing approaches rely either on…

Artificial Intelligence · Computer Science 2025-11-21 Pantelis Dogoulis , Fabien Bernier , Félix Fourreau , Karim Tit , Maxime Cordy

Standard sparse pseudo-input approximations to the Gaussian process (GP) cannot handle complex functions well. Sparse spectrum alternatives attempt to answer this but are known to over-fit. We suggest the use of variational inference for…

Machine Learning · Statistics 2015-03-23 Yarin Gal , Richard Turner

We consider a population with two types of individuals, distinguished by the resources required for reproduction: type-$0$ (small) individuals need a fractional resource unit of size $\vartheta \in (0,1)$, while type-$1$ (large) individuals…

Probability · Mathematics 2025-10-29 Gerold Alsmeyer , Fernando Cordero , Hannah Dopmeyer

Path integrals are a central tool when it comes to describing quantum or thermal fluctuations of particles or fields. Their success dates back to Feynman who showed how to use them within the framework of quantum mechanics. Since then, path…

Statistical Mechanics · Physics 2022-08-31 Leticia F. Cugliandolo , Vivien Lecomte , Frédéric Van Wijland

This paper presents a rigorous theoretical convergence analysis of the Wirtinger Flow (WF) algorithm for Poisson phase retrieval, a fundamental problem in imaging applications. Unlike prior analyses that rely on truncation or additional…

Numerical Analysis · Mathematics 2025-01-14 Bing Gao , Ran Gu , Shigui Ma

We study a linear-fractional Bienaym\'e-Galton-Watson process with a general type space. The corresponding tree contour process is described by an alternating random walk with the downward jumps having a geometric distribution. This leads…

Probability · Mathematics 2016-03-07 Alexey Lindo , Serik Sagitov

In this article, we deal with the efficient computation of the Wright function in the cases of interest for the expression of solutions of some fractional differential equations. The proposed algorithm is based on the inversion of the…

Numerical Analysis · Mathematics 2024-09-16 Lidia Aceto , Fabio Durastante

A deterministic temporal process can be determined by its trajectory, an element in the product space of (a) initial condition $z_0 \in \mathcal{Z}$ and (b) transition function $f: (\mathcal{Z}, \mathcal{T}) \to \mathcal{Z}$ often…

Machine Learning · Computer Science 2024-03-19 Jurijs Nazarovs , Zhichun Huang , Xingjian Zhen , Sourav Pal , Rudrasis Chakraborty , Vikas Singh

The crucial step in designing a particle filter for a particular application is the choice of importance density. The optimal scheme is to use the conditional posterior density of the state, but this cannot be sampled or calculated…

Computation · Statistics 2014-08-15 Pete Bunch , Simon Godsill

Diffusion is a key element of a large set of phenomena occurring on natural and social systems modeled in terms of complex weighted networks. Here, we introduce a general formalism that allows to easily write down mean-field equations for…

Statistical Mechanics · Physics 2010-07-14 Andrea Baronchelli , Romualdo Pastor-Satorras

Mean-field molecular dynamics based on path integrals is used to approximate canonical quantum observables for particle systems consisting of nuclei and electrons. A computational bottleneck is the sampling from the Gibbs density of the…

Numerical Analysis · Mathematics 2023-11-30 Xin Huang , Petr Plechac , Mattias Sandberg , Anders Szepessy

The committor functions are central to investigating rare but important events in molecular simulations. It is known that computing the committor function suffers from the curse of dimensionality. Recently, using neural networks to estimate…

Machine Learning · Statistics 2025-01-28 Yueyang Wang , Kejun Tang , Xili Wang , Xiaoliang Wan , Weiqing Ren , Chao Yang

We derive a semi-analytical form for the Wigner transform for the canonical density operator of a discrete system coupled to a harmonic bath based on the path integral expansion of the Boltzmann factor. The introduction of this simple and…

Chemical Physics · Physics 2017-02-01 Andrés Montoya-Castillo , David R. Reichman

In this paper we present a general, axiomatical framework for the rigorous approximation of invariant densities and other important statistical features of dynamics. We approximate the system trough a finite element reduction, by composing…

Dynamical Systems · Mathematics 2023-04-05 Stefano Galatolo , Maurizio Monge , Isaia Nisoli , Federico Poloni

We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele frequency dynamics…

Populations and Evolution · Quantitative Biology 2019-09-18 Marnus Stoltz , Boris Bauemer , Remco Bouckaert , Colin Fox , Gordon Hiscott , David Bryant

This paper provides a formulation of the log-homotopy particle flow from the perspective of variational inference. We show that the transient density used to derive the particle flow follows a time-scaled trajectory of the Fisher-Rao…

Machine Learning · Statistics 2026-03-06 Yinzhuang Yi , Jorge Cortés , Nikolay Atanasov

Although real-world complex systems typically interact through sparse and heterogeneous networks, analytic solutions of their dynamics are limited to models with all-to-all interactions. Here, we solve the dynamics of a broad range of…

Disordered Systems and Neural Networks · Physics 2025-01-28 Fernando L. Metz
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