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Drift analysis aims at translating the expected progress of an evolutionary algorithm (or more generally, a random process) into a probabilistic guarantee on its run time (hitting time). So far, drift arguments have been successfully…

Neural and Evolutionary Computing · Computer Science 2021-11-01 Benjamin Doerr , Timo Kötzing

To model discrete sequences such as DNA, proteins, and language using diffusion, practitioners must choose between three major methods: diffusion in discrete space, Gaussian diffusion in Euclidean space, or diffusion on the simplex. Despite…

We present a new adaptive algorithm for learning discrete distributions under distribution drift. In this setting, we observe a sequence of independent samples from a discrete distribution that is changing over time, and the goal is to…

Machine Learning · Computer Science 2024-03-11 Alessio Mazzetto

In this paper we introduce a randomized version of the backward Euler method, that is applicable to stiff ordinary differential equations and nonlinear evolution equations with time-irregular coefficients. In the finite-dimensional case, we…

Numerical Analysis · Mathematics 2022-05-10 Monika Eisenmann , Mihály Kovács , Raphael Kruse , Stig Larsson

Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coefficients from data remains challenging. Standard approaches often rely on short-time…

Machine Learning · Statistics 2026-04-28 Ludovico T. Giorgini

We introduce a theory of sequential causal inference in which learners in a chain estimate a structural model from their upstream teacher and then pass samples from the model to their downstream student. It extends the population dynamics…

Populations and Evolution · Quantitative Biology 2012-02-28 James P. Crutchfield , Sean Whalen

For multivariant Wright-Fisher models in population genetics, we introduce equilibrium states, expressed by fluctuations of probability ratio, in contrast to the traditionally used fluctuations, expressed by the difference between the…

Statistics Theory · Mathematics 2020-08-04 D. Koroliouk , V. S. Koroliuk

In this article, we construct and analyse an explicit numerical splitting method for a class of semi-linear stochastic differential equations (SDEs) with additive noise, where the drift is allowed to grow polynomially and satisfies a global…

Numerical Analysis · Mathematics 2022-02-04 Evelyn Buckwar , Adeline Samson , Massimiliano Tamborrino , Irene Tubikanec

We study a one-dimensional spatial population model where the population sizes at each site are chosen according to a translation invariant and ergodic distribution and are uniformly bounded away from 0 and infinity. We suppose that the…

Probability · Mathematics 2019-06-14 Raphaël Forien

We study parameter estimation for univariate stochastic differential equations with locally Lipschitz drift and H\"older continuous multiplicative diffusion, a class commonly arising in several applications. Existing inference methods…

Methodology · Statistics 2026-05-19 Bowen Fang , Dario Spanò , Massimiliano Tamborrino

An improved diffuse boundary condition, where the number flux of the incoming real molecules on the wall surface is calculated using the molecular variables rather than the cell's macroscopic variables, is proposed to eliminate the…

Computational Physics · Physics 2014-03-18 Jun Li

Diffusion models have become the go-to method for large-scale generative models in real-world applications. These applications often involve data distributions confined within bounded domains, typically requiring ad-hoc thresholding…

Machine Learning · Statistics 2024-01-09 Wei Deng , Yu Chen , Nicole Tianjiao Yang , Hengrong Du , Qi Feng , Ricky T. Q. Chen

A system with equation and dynamic boundary condition of Cahn-Hilliard type is considered. This system comes from a derivation performed in Liu-Wu (Arch. Ration. Mech. Anal. 233 (2019), 167--247) via an energetic variational approach.…

Analysis of PDEs · Mathematics 2022-08-02 Pierluigi Colli , Takeshi Fukao , Luca Scarpa

We are interested in the numerical approximation of non-linear stochastic differential equations (SDEs) with solution in a certain domain. Our goal is to construct explicit numerical schemes that preserve that structure. We generalize the…

Numerical Analysis · Mathematics 2017-06-28 Ioannis S. Stamatiou

We introduce a general framework for enforcing local or global maximum principles in high-order space-time discretizations of a scalar hyperbolic conservation law. We begin with sufficient conditions for a space discretization to be bound…

Numerical Analysis · Mathematics 2021-06-14 Dmitri Kuzmin , Manuel Quezada de Luna , David I. Ketcheson , Johanna Grüll

This work presents a randomized-tamed Milstein scheme for stochastic differential equations whose drift coefficient exhibits superlinear growth in the state variable and limited temporal regularity, quantified by $\beta$-H\"older continuity…

Numerical Analysis · Mathematics 2026-01-15 Sani Biswas

An implicit Euler finite-volume scheme for an $n$-species population cross-diffusion system of Shigesada--Kawasaki--Teramoto-type in a bounded domain with no-flux boundary conditions is proposed and analyzed. The scheme preserves the formal…

Numerical Analysis · Mathematics 2020-11-18 Antoine Zurek , Ansgar Jüngel

A classical pseudodifferential operator $P$ on $R^n$ satisfies the $\mu$-transmission condition relative to a smooth open subset $\Omega $, when the symbol terms have a certain twisted parity on the normal to $\partial\Omega $. As shown…

Analysis of PDEs · Mathematics 2016-01-20 Gerd Grubb

We present strongly stable semi-discrete finite difference approximations to the quarter space problem (x>0, t>0) for the first order in time, second order in space wave equation with a shift term. We consider space-like (pure outflow) and…

General Relativity and Quantum Cosmology · Physics 2024-07-11 Gioel Calabrese , Carsten Gundlach

Kruse and Wu [Math. Comp. 88 (2019) 2793--2825] proposed a fully discrete randomized Galerkin finite element method for semilinear stochastic evolution equations (SEEs) driven by additive noise and showed that this method attains a temporal…

Numerical Analysis · Mathematics 2026-02-12 Xiao Qi , Yue Wu , Yubin Yan