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We analyse a proposition which considers quantum theory as a mere tool for calculating probabilities for sequences of outcomes of observations made by an Observer, who him/herself remains outside the scope of the theory. Predictions are…

Quantum Physics · Physics 2020-05-27 D. Sokolovski

The execution time of programs is a key element in many areas of computer science, mainly those where achieving good performance (e.g., scheduling in cloud computing) or a predictable one (e.g., meeting deadlines in embedded systems) is the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-13 Matheus Henrique Junqueira Saldanha

We consider the problem of forecasting complex, nonlinear space-time processes when observations provide only partial information of on the system's state. We propose a natural data-driven framework, where the system's dynamics are modelled…

Systems and Control · Computer Science 2019-03-01 Ibrahim Ayed , Emmanuel de Bézenac , Arthur Pajot , Julien Brajard , Patrick Gallinari

The non-stationary Erlang-A queue is a fundamental queueing model that is used to describe the dynamic behavior of large scale multi-server service systems that may experience customer abandonments, such as call centers, hospitals, and…

Probability · Mathematics 2026-01-14 Andrew Daw , Jamol Pender

A case is made that researchers are interested in studying processes. Often the inferences they are interested in making are about the process and its associated population. On other occasions, a researcher may be interested in making an…

Other Statistics · Statistics 2022-06-20 Charles W. Champ , Andrew V. Sills

We introduce a framework for the description of a large class of delay-differential algebraic systems, in which we study three core problems: first we characterize abstractly the well-posedness of the initial-value problem, then we design a…

Dynamical Systems · Mathematics 2017-07-11 Sébastien Boisgérault

A method to construct Hamiltonian theories for systems of both ordinary and partial differential equations is presented. The knowledge of a Lagrangian is not at all necessary to achieve the result. The only ingredients required for the…

High Energy Physics - Theory · Physics 2007-05-23 Sergio A. Hojman

We study a generalization of the voter model on complex networks, focusing on the scaling of mean exit time. Previous work has defined the voter model in terms of an initially chosen node and a randomly chosen neighbor, which makes it…

Statistical Mechanics · Physics 2015-05-13 Casey M. Schneider-Mizell , Leonard M. Sander

We develop a methodology to learn finitely generated random iterated function systems from time-series of partial observations using delay embeddings. We obtain a minimal model representation for the observed dynamics, using a hidden…

Dynamical Systems · Mathematics 2025-08-20 Emilia Gibson , Jeroen S. W. Lamb

Motivated by applications that involve setting proper staffing levels for multi-server queueing systems with batch arrivals, we present a thorough study of the queue-length process $\{Q(t); t \geq 0\}$, departure process $\{D(t); t \geq…

Probability · Mathematics 2022-06-20 Andrew Daw , Brian Fralix , Jamol Pender

The aim of this paper is the analysis of the fractional Poisson process where the state probabilities $p_k^{\nu_k}(t)$, $t\ge 0$, are governed by time-fractional equations of order $0<\nu_k\leq 1$ depending on the number $k$ of events…

Probability · Mathematics 2015-09-21 Roberto Garra , Enzo Orsingher , Federico Polito

Panel data arise when time series measurements are collected from multiple, dynamically independent but structurally related systems. Each system's time series can be modeled as a partially observed Markov process (POMP), and the ensemble…

Methodology · Statistics 2025-11-13 Carles Bretó , Jesse Wheeler , Aaron A. King , Edward L. Ionides

It is a very hard task to compute an exact solution for the differential equations, with differences, system that allows the determination of the M|M|m|m system transient probabilities. The respective complexity grows with m. The…

Probability · Mathematics 2023-12-08 Manuel Alberto M. Ferreira

Group elevator scheduling is an NP-hard sequential decision-making problem with unbounded state spaces and substantial uncertainty. Decision-theoretic reasoning plays a surprisingly limited role in fielded systems. A new opportunity for…

Artificial Intelligence · Computer Science 2012-12-12 Daniel N. Nikovski , Matthew Brand

The election is a classical problem in distributed algorithmic. It aims to design and to analyze a distributed algorithm choosing a node in a graph, here, in a tree. In this paper, a class of randomized algorithms for the election is…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-20 Jean-François Marckert , Nasser Saheb-Djahromi , Akka Zemmari

This paper presents a general approach to linear stochastic processes driven by various random noises. Mathematically, such processes are described by linear stochastic differential equations of arbitrary order (the simplest non-trivial…

Condensed Matter · Physics 2009-10-28 Alon Drory

The distribution of waiting times until the occurrence of a critical event is a crucial statistical problem across several disciplines in Science. In this work we present a statistical model in which a relevant quantity X accumulates until…

Applications · Statistics 2021-01-12 Vivianne Olguín-Arias , Sergio Davis , Gonzalo Gutiérrez

This Ph.D. thesis concerns the version of the classical coupon collector's problem, when a collector samples with replacement a set of $n\ge 2$ distinct coupons so that at each time any one of the $n$ coupons is drawn with the same…

Probability · Mathematics 2010-07-27 Anna Pósfai

Mathematical theory of selection is developed within the frameworks of general models of inhomogeneous populations with continuous time. Methods that allow us to study the distribution dynamics under natural selection and to construct…

Populations and Evolution · Quantitative Biology 2009-12-22 Georgy P. Karev

We develop a qualitative theory of Markov Decision Processes (MDPs) and Partially Observable MDPs that can be used to model sequential decision making tasks when only qualitative information is available. Our approach is based upon an…

Artificial Intelligence · Computer Science 2013-01-07 Blai Bonet , Judea Pearl