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Mouse-tracking recording techniques are becoming very attractive in experimental psychology. They provide an effective means of enhancing the measurement of some real-time cognitive processes involved in categorization, decision-making, and…

Applications · Statistics 2019-12-18 Antonio Calcagnì , Luigi Lombardi , Marco D'Alessandro

This paper proposes a general framework for constructing feedback controllers that drive complex dynamical systems to "efficient" steady-state (or slowly varying) operating points. Efficiency is encoded using generalized equations which can…

A real-time path integral Monte Carlo approach is developed to study the dynamics in a many-body quantum system until reaching a nonequilibrium stationary state. The approach is based on augmenting an exact reduced equation for the…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Lothar Mühlbacher , Eran Rabani

This article discusses a new technique to automatically generate test cases for object oriented programs. At the state of the art, the problem of generating adequate sets of complete test cases has not been satisfactorily solved yet. There…

Software Engineering · Computer Science 2020-05-20 Matteo Modonato

Designing a network (e.g., a telecommunication or transport network) is mainly done offline, in a planning phase, prior to the operation of the network. On the other hand, a massive effort has been devoted to characterizing dynamic…

Artificial Intelligence · Computer Science 2026-04-01 Duo Wang , Andrea Araldo , Mounim El Yacoubi

We investigate the presence of static solutions in models described by real scalar field in two-dimensional spacetime. After taking advantage of a procedure introduced sometime ago, we solve intricate nonlinear ordinary differential…

High Energy Physics - Theory · Physics 2014-09-25 D. Bazeia , L. Losano , M. A. Marques , R. Menezes

Given a series of photographs taken during a Go game, we describe the techniques we successfully employ for pinpointing the grid lines of the Go board and for tracking their small movements between consecutive photographs; then we discuss…

Computer Vision and Pattern Recognition · Computer Science 2018-04-23 Mario Corsolini , Andrea Carta

Sequential decision problems are often approximately solvable by simulating possible future action sequences. Metalevel decision procedures have been developed for selecting which action sequences to simulate, based on estimating the…

Artificial Intelligence · Computer Science 2014-08-12 Nicholas Hay , Stuart Russell , David Tolpin , Solomon Eyal Shimony

The widespread availability of superhuman AI engines is changing how we play the ancient game of Go. The open-source software packages developed after the AlphaGo series shifted focus from producing strong playing entities to providing…

Artificial Intelligence · Computer Science 2020-11-16 Attila Egri-Nagy , Antti Törmänen

The topic of statistical inference for dynamical systems has been studied extensively across several fields. In this survey we focus on the problem of parameter estimation for non-linear dynamical systems. Our objective is to place results…

Statistics Theory · Mathematics 2012-06-19 Kevin McGoff , Sayan Mukherjee , Natesh S. Pillai

We introduce a stacking version of the Monte Carlo algorithm in the context of option pricing. Introduced recently for aeronautic computations, this simple technique, in the spirit of current machine learning ideas, learns control variates…

Computational Finance · Quantitative Finance 2019-03-27 Antoine Jacquier , Emma R. Malone , Mugad Oumgari

A canonical formalism and constraint analysis for discrete systems subject to a variational action principle are devised. The formalism is equivalent to the covariant formulation, encompasses global and local discrete time evolution moves…

Mathematical Physics · Physics 2013-09-17 Bianca Dittrich , Philipp A Hoehn

Stability is among the most important concepts in dynamical systems. Local stability is well-studied, whereas determining how "globally stable" a nonlinear system is very challenging. Over the last few decades, many different ideas have…

Dynamical Systems · Mathematics 2022-10-10 Hana Krakovská , Christian Kühn , Iacopo P. Longo

This paper studies the dynamic programming principle using the measurable selection method for stochastic control of continuous processes. The novelty of this work is to incorporate intermediate expectation constraints on the canonical…

Optimization and Control · Mathematics 2020-04-22 Yuk-Loong Chow , Xiang Yu , Chao Zhou

Hysteresis can be defined from a dynamical systems perspective with respect to equilibrium points. Consequently, hysteresis naturally lends itself as a topic to illustrate and extend concepts in a dynamical systems course. A number of…

Dynamical Systems · Mathematics 2022-05-25 Amenda Chow , Kristen A. Morris , Gina Faraj Rabbah

The paper introduces a general framework for statistical analysis of functional time series from a Bayesian perspective. The proposed approach, based on an extension of the popular dynamic linear model to Banach-space valued observations…

Methodology · Statistics 2013-12-02 Giovanni Petris

The concepts of probability, statistics and stochastic theory are being successfully used in structural engineering. Markov Chain modelling is a simple stochastic process model that has found its application in both describing stochastic…

Applications · Statistics 2007-08-14 K. Balaji Rao

In this paper we consider the possibility to use numerical simulations for a computer assisted analysis of integrability of dynamical systems. We formulate a rather general method of recovering the obstruction to integrability for the…

Dynamical Systems · Mathematics 2014-11-18 Vladimir Salnikov

In this paper, I present a summary on some works that utilized static analysis techniques for understanding biological systems. Control flow analysis, context dependent analysis, and other techniques were employed to investigate the…

Computational Engineering, Finance, and Science · Computer Science 2015-01-05 A. Aziz Altowayan

We propose dynamical systems trees (DSTs) as a flexible class of models for describing multiple processes that interact via a hierarchy of aggregating parent chains. DSTs extend Kalman filters, hidden Markov models and nonlinear dynamical…

Machine Learning · Computer Science 2012-07-19 Andrew Howard , Tony S. Jebara
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