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In many modern applications, discretely-observed data may be naturally understood as a set of functions. Functional data often exhibit two confounded sources of variability: amplitude (y-axis) and phase (x-axis). The extraction of amplitude…

Methodology · Statistics 2025-05-22 Yoonji Kim , Oksana A. Chkrebtii , Sebastian A. Kurtek

Statistical quality control methods are noteworthy to producing standard production in manufacturing processes. In this regard, there are many classical manners to control the process. Many of them have a global assumption around the…

Recent advances in learning-based control leverage deep function approximators, such as neural networks, to model the evolution of controlled dynamical systems over time. However, the problem of learning a dynamics model and a stabilizing…

Systems and Control · Electrical Eng. & Systems 2023-04-05 Youngjae Min , Spencer M. Richards , Navid Azizan

We focus on variational inference in dynamical systems where the discrete time transition function (or evolution rule) is modelled by a Gaussian process. The dominant approach so far has been to use a factorised posterior distribution,…

Machine Learning · Statistics 2018-12-17 Alessandro Davide Ialongo , Mark van der Wilk , James Hensman , Carl Edward Rasmussen

Proper modeling of complex systems requires innovative mathematical tools. In this sense, we sought to use deformed or fractal derivatives for studying the dynamics of systems, particularly those, such as granular gases, in which the…

Statistical Mechanics · Physics 2024-06-27 José Weberszpil , Cresus F. de L. Godinho , Ion Vasile Vancea

Demand functions for goods are generally cyclical in nature with characteristics such as trend or stochasticity. Most existing demand forecasting techniques in literature are designed to manage and forecast this type of demand functions.…

Applications · Statistics 2011-10-04 Murphy Choy , Michelle L. F. Cheong

Direct correlation functions (DCFs), linked to the second functional derivative of the free energy with respect to the one-particle density, play a fundamental role in a statistical mechanics description of matter. This holds in particular…

Soft Condensed Matter · Physics 2021-08-25 S. -C. Lin , M. Oettel , J. M. Hring , R. Haussmann , M. Fuchs , G. Kahl

A wide variety of data can be represented using third-order tensors, spanning applications in chemometrics, psychometrics, and image processing. However, traditional data-driven frameworks are not naturally equipped to process tensors…

Systems and Control · Electrical Eng. & Systems 2024-10-29 Xin Mao , Anqi Dong , Ziqin He , Yidan Mei , Can Chen

We find all factorized duality functions for a class of interacting particle systems. The functions we recover are self-duality functions for interacting particle systems such as zero-range processes, symmetric inclusion and exclusion…

Probability · Mathematics 2018-08-01 Frank Redig , Federico Sau

One of the basic frameworks in science views behavioral products as a process within a dynamic system. The mechanism might be seen as a representation of many instances of centralized control in real time. Many real systems, however,…

Dynamical Systems · Mathematics 2019-08-19 Chulwook Park

This paper deals with a special type of Lyapunov functions, namely the solution of Zubov's equation. Such a function can be used to characterize the domain of attraction for systems of ordinary differential equations. We derive and prove an…

Dynamical Systems · Mathematics 2021-12-30 Wei Kang , Kai Sun , Liang Xu

For a series of Markov processes we prove stochastic duality relations with duality functions given by orthogonal polynomials. This means that expectations with respect to the original process (which evolves the variable of the orthogonal…

Probability · Mathematics 2017-02-01 Chiara Franceschini , Cristian Giardinà

The report considers the dynamics of the global population as the unique case of the Socio-Economic Soft Matter system. This category was introduced for complex systems dominated by mesoscale assemblies, emerging due to the inherent…

Physics and Society · Physics 2022-09-07 Agata Angelika Rzoska , Aleksandra Drozd-Rzoska

Temporal data such as time series can be viewed as discretized measurements of the underlying function. To build a generative model for such data we have to model the stochastic process that governs it. We propose a solution by defining the…

Machine Learning · Computer Science 2023-05-22 Marin Biloš , Kashif Rasul , Anderson Schneider , Yuriy Nevmyvaka , Stephan Günnemann

We introduce a novel stochastic growth process, the record-driven growth process, which originates from the analysis of a class of growing networks in a universal limiting regime. Nodes are added one by one to a network, each node…

Statistical Mechanics · Physics 2008-11-12 C. Godreche , J. M. Luck

We have shown recently that a Markov process conditioned on rare events involving time-integrated random variables can be described in the long-time limit by an effective Markov process, called the driven process, which is given…

Statistical Mechanics · Physics 2015-12-17 Raphael Chetrite , Hugo Touchette

The field of hypothesis generation promises to reduce costs in neuroscience by narrowing the range of interventional studies needed to study various phenomena. Existing machine learning methods can generate scientific hypotheses from…

Machine Learning · Computer Science 2025-07-04 Zachary C. Brown , David Carlson

A practical statistical analysis on the regional populations and GDPs of China is conducted. The result shows that the distribution of the populations and that of the GDPs obeys the shifted power law, respectively. To understand these…

Physics and Society · Physics 2018-02-14 Jie Huo , Xu-Ming Wang , Rui Hao , Peng Wang

The direct sampling method proposed by Walker et al. (JCGS 2011) can generate draws from weighted distributions possibly having intractable normalizing constants. The method may be of interest as a useful tool in situations which require…

Computation · Statistics 2024-01-19 Andrew M. Raim

In practice , quite often there is a need to describe the values set by means of a table in the form of some functional dependence . The observed values , due to certain circumstances , have an error . For approximation, it is advisable to…

Econometrics · Economics 2023-07-28 Yekimov Sergey