English
Related papers

Related papers: Diffusion approximation of controlled branching pr…

200 papers

We consider a broad class of continuous-time two-type population size-dependent Markov Branching Processes. The offspring distribution can depend on the current (alive) and total (dead and alive) populations. Using stochastic approximation…

Probability · Mathematics 2023-04-04 Khushboo Agarwal , Veeraruna Kavitha

Continuous time Bayesian networks (CTBNs) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cyclic) dependency graph over a set of variables, each of which…

Artificial Intelligence · Computer Science 2012-07-09 Uri Nodelman , Daphne Koller , Christian R. Shelton

In this article we prove a new central limit theorem (CLT) for coupled particle filters (CPFs). CPFs are used for the sequential estimation of the difference of expectations w.r.t. filters which are in some sense close. Examples include the…

Statistics Theory · Mathematics 2026-01-14 Ajay Jasra , Fangyuan Yu

In this work, we consider a modification of the usual Branching Random Walk (BRW), where we give certain independent and identically distributed (i.i.d.) displacements to all the particles at the $n$-th generation, which may be different…

Probability · Mathematics 2025-02-18 Antar Bandyopadhyay , Partha Pratim Ghosh

In this work, we study asymptotics of the genealogy of Galton-Watson processes. Thus we consider a offspring distribution such that the rescaled Galton-Watson processes converges to a continuous state branching process (CSBP) with jumps.…

Probability · Mathematics 2017-06-20 Ibrahima Drame , Etienne Pardoux

The asymptotic behavior, as $n\rightarrow \infty $ of the probability of the event that a decomposable critical branching process $\mathbf{Z}(m)=(Z_{1}(m),...,Z_{N}(m)),$ $m=0,1,2,...,$ with $N$ types of particles dies at moment $n$ is…

Probability · Mathematics 2015-04-21 Vladimir Vatutin , Elena Dyakonova

We introduce and study a class of probabilistic generative models, where the latent object is a finite-dimensional diffusion process on a finite time interval and the observed variable is drawn conditionally on the terminal point of the…

Probability · Mathematics 2019-06-03 Belinda Tzen , Maxim Raginsky

In this paper, we consider a diffusion process pertaining to a chain of distributed control systems with small random perturbation. The distributed control system is formed by n subsystems that satisfy an appropriate Hormander condition,…

Dynamical Systems · Mathematics 2014-09-04 Getachew K. Befekadu , Panos J. Antsaklis

We consider continuous-state branching processes (CB processes) which become extinct almost surely. First, we tackle the problem of describing the stationary measures on $(0,+\infty)$ for such CB processes. We give a representation of the…

Probability · Mathematics 2025-04-30 Rongli Liu , Yan-Xia Ren , Ting Yang

In this work, several convergence results are established for nearly critical self-excited systems in which event arrivals are described by multivariate marked Hawkes point processes. Under some mild high-frequency assumptions, the rescaled…

Probability · Mathematics 2024-01-31 Wei Xu

We consider a controlled-diffusion process pertaining to a chain of distributed systems with random perturbations that satisfies a weak H\"ormander type condition. In particular, we consider a stochastic control problem with the following…

Optimization and Control · Mathematics 2015-09-29 Getachew K. Befekadu , Eduardo L. Pasiliao

A population genetics model based on a multitype branching process, or equivalently a Galton-Watson branching process for multiple alleles, is pre- sented. The diffusion limit forward Kolmogorov equation is derived for the case of neutral…

Populations and Evolution · Quantitative Biology 2018-02-21 Conrad J. Burden , Yi Wei

A curious connection exists between the theory of optimal stopping for independent random variables, and branching processes. In particular, for the branching process $Z_n$ with offspring distribution $Y$, there exists a random variable $X$…

Probability · Mathematics 2007-05-23 David Assaf , Larry Goldstein , Ester Samuel-Cahn

Temporal point processes offer a powerful framework for sampling from discrete distributions, yet they remain underutilized in existing literature. We show how to construct, for any target multivariate count distribution with…

Computation · Statistics 2026-05-19 Cameron A. Stewart , Maneesh Sahani

We consider a multi-type Galton-Watson branching processes, where the largest in magnitude positive eigenvalue $\rho$ of the first moments matrix is close to unity. Specifically, we examine the random vector representing the number of…

Probability · Mathematics 2024-07-24 T. B. Lysetskyi , Ya. I. Yeleiko

This article gives an overview of the developments in controlled diffusion processes, emphasizing key results regarding existence of optimal controls and their characterization via dynamic programming for a variety of cost criteria and…

Probability · Mathematics 2007-05-23 Vivek S. Borkar

Belief Propagation (BP) is a simple probabilistic inference algorithm, consisting of passing messages between nodes of a graph representing a probability distribution. Its analogy with a neural network suggests that it could have…

Artificial Intelligence · Computer Science 2024-03-20 Vincent Bouttier , Renaud Jardri , Sophie Deneve

The stationary asymptotic properties of the diffusion limit of a multi-type branching process with neutral mutations are studied. For the critical and subcritical processes the interesting limits are those of quasi-stationary distributions…

Probability · Mathematics 2022-04-08 Conrad J. Burden , Robert C. Griffiths

We study the explosion phenomenon of nonlinear continuous-state branching processes (nonlinear CSBPs). First an explicit integral test for explosion is designed when the rate function does not increase too fast. We then exhibit three…

Probability · Mathematics 2024-04-10 Bo Li , Clément Foucart , Xiaowen Zhou

The term ``sequential Monte Carlo methods'' or, equivalently, ``particle filters,'' refers to a general class of iterative algorithms that performs Monte Carlo approximations of a given sequence of distributions of interest (\pi_t). We…

Statistics Theory · Mathematics 2007-06-13 Nicolas Chopin
‹ Prev 1 3 4 5 6 7 10 Next ›