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We develop an automated variational method for inference in models with Gaussian process (GP) priors and general likelihoods. The method supports multiple outputs and multiple latent functions and does not require detailed knowledge of the…

Machine Learning · Statistics 2018-11-06 Edwin V. Bonilla , Karl Krauth , Amir Dezfouli

Consider a continuous time particle system $\eta^t=(\eta^t(k),k\in \mathbb{L})$, indexed by a lattice $\mathbb{L}$ which will be either $\mathbb{Z}$, $\mathbb{Z}/n\mathbb{Z}$, a segment $\{1,\cdots, n\}$, or $\mathbb{Z}^d$, and taking its…

Probability · Mathematics 2019-01-11 Luis Fredes , Jean-François Marckert

The time evolution of a bounded quantum system is considered in the framework of the orthogonal, unitary and symplectic circular ensembles of random matrix theory. For an $N$ dimensional Hilbert space we prove that in the large $N$ limit…

Mesoscale and Nanoscale Physics · Physics 2008-02-03 P. Leboeuf , G. Iacomelli

This paper studies the properties of the Multiply Iterated Poisson Process (MIPP), a stochastic process constructed by repeatedly time-changing a Poisson process, and its applications in ruin theory. Like standard Poisson processes, MIPPs…

Probability · Mathematics 2025-05-13 Dongdong Hu , Svetlozar T. Rachev , Hasanjan Sayit , Hailiang Yang , Yildiray Yildirim

We propose a discrete-time, finite-state stationary process that can possess long-range dependence. Among the interesting features of this process is that each state can have different long-term dependency, i.e., the indicator sequence can…

Probability · Mathematics 2022-09-19 Jeonghwa Lee

Scattering moments provide nonparametric models of random processes with stationary increments. They are expected values of random variables computed with a nonexpansive operator, obtained by iteratively applying wavelet transforms and…

Methodology · Statistics 2015-03-17 Joan Bruna , Stéphane Mallat , Emmanuel Bacry , Jean-François Muzy

We consider some versions and generalizations of an approach to the expansion of iterated Ito stochastic integrals of arbitrary multiplicity $k$ $(k\in\mathbb{N})$ based on generalized multiple Fourier series. Expansions of iterated…

Probability · Mathematics 2023-08-01 Dmitriy F. Kuznetsov

We analyse and explain the increased generalisation performance of iterate averaging using a Gaussian process perturbation model between the true and batch risk surface on the high dimensional quadratic. We derive three phenomena…

Machine Learning · Statistics 2021-11-02 Diego Granziol , Xingchen Wan , Samuel Albanie , Stephen Roberts

Some classes of increment martingales, and the corresponding localized classes, are studied. An increment martingale is indexed by the real line and its increment processes are martingales. We focus primarily on the behavior as time goes to…

Probability · Mathematics 2015-03-17 Andreas Basse-O'Connor , Svend-Erik Graversen , Jan Pedersen

We study general properties for the family of stochastic processes with polynomial regression property, that is that every conditional moment of the process is a polynomial. It turns out that then there exists a family of polynomial…

Probability · Mathematics 2017-04-04 Paweł J. Szabłowski

We study the limiting behavior of continuous time trawl processes which are defined using an infinitely divisible random measure of a time dependent set. In this way one is able to define separately the marginal distribution and the…

Probability · Mathematics 2017-08-10 Danijel Grahovac , Nikolai N. Leonenko , Murad S. Taqqu

Autocorrelations in MCMC chains increase the variance of the estimators they produce. We propose the occlusion process to mitigate this problem. It is a process that sits upon an existing MCMC sampler, and occasionally replaces its samples…

Computation · Statistics 2024-11-20 Max Hird , Florian Maire

The class of index-mixed copulas is introduced and its properties are investigated. Index-mixed copulas are constructed from given base copulas and a random index vector, and show a rather remarkable degree of analytical tractability. The…

Methodology · Statistics 2023-08-10 Klaus Herrmann , Marius Hofert , Nahid Sadr

We characterize the class of exchangeable Feller processes evolving on partitions with boundedly many blocks. In continuous-time, the jump measure decomposes into two parts: a $\sigma$-finite measure on stochastic matrices and a collection…

Probability · Mathematics 2014-09-04 Harry Crane

We describe a measurement device principle based on discrete iterations of Bayesian updating of system state probability distributions. Although purely classical by nature, these measurements are accompanied with a progressive collapse of…

Mathematical Physics · Physics 2015-06-11 Michel Bauer , Denis Bernard , Tristan Benoist

Temporal Point Processes (TPP) are probabilistic generative frameworks. They model discrete event sequences localized in continuous time. Generally, real-life events reveal descriptive information, known as marks. Marked TPPs model time and…

Machine Learning · Computer Science 2024-11-26 Govind Waghmare , Ankur Debnath , Siddhartha Asthana , Aakarsh Malhotra

Reinforced Galton--Watson processes describe the dynamics of a population where reproduction events are reinforced, in the sense that offspring numbers of forebears can be repeated randomly by descendants. More specifically, the evolution…

Probability · Mathematics 2025-02-24 Jean Bertoin , Bastien Mallein

A new fractional non-homogeneous counting process has been introduced and developed using the Kilbas and Saigo three-parameter generalization of the Mittag-Leffler function. The probability distribution function of this process reproduces…

Probability · Mathematics 2024-01-01 Nick Laskin

In a series of recent works, an interesting quantum generative model based on parameterized instantaneous polynomial quantum (IQP) circuits has emerged as they can be trained efficiently classically using any loss function that depends only…

Quantum Physics · Physics 2025-04-09 Andrii Kurkin , Kevin Shen , Susanne Pielawa , Hao Wang , Vedran Dunjko

Continuation refers to the operation by which the cumulative distribution function of a discontinuous random vector is made continuous through multilinear interpolation. The copula that results from the application of this technique to the…

Statistics Theory · Mathematics 2014-07-07 Christian Genest , Johanna G. Nešlehová , Bruno Rémillard
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