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Causal inference is central to many areas of artificial intelligence, including complex reasoning, planning, knowledge-base construction, robotics, explanation, and fairness. An active community of researchers develops and enhances…

Artificial Intelligence · Computer Science 2019-11-05 Amanda Gentzel , Dan Garant , David Jensen

Moment closure methods appear in myriad scientific disciplines in the modelling of complex systems. The goal is to achieve a closed form of a large, usually even infinite, set of coupled differential (or difference) equations. Each equation…

Statistical Mechanics · Physics 2018-12-24 Christian Kuehn

Numerical simulations based on electronic structure calculations are finding ever growing applications in many areas of physics. A major limiting factor is however the cubic scaling of the algorithms used. Building on previous work [F. R.…

Materials Science · Physics 2009-11-11 Florian R. Krajewski , Michele Parrinello

In the field of structural engineering analysis, a common requirement is to calculate the modal frequencies of a structure that has undergone an update, either naturally (such as from material degradation), or due to man-made influences (by…

Optimization and Control · Mathematics 2020-08-25 P. Cheema , M. M. Alamdari , G. A. Vio

Multiscale modeling of material properties has emerged as one of the grand challenges in material science and engineering. We provide a comprehensive, though not exhaustive, overview of the current status of multiscale simulations of…

Materials Science · Physics 2007-05-23 Gang Lu , Efthimios Kaxiras

Data-collapse is a way of establishing scaling and extracting associated exponents in problems showing self-similar or self-affine characteristics as e.g. in equilibrium or non-equilibrium phase transitions, in critical phases, in dynamics…

Soft Condensed Matter · Physics 2009-11-07 Somendra M. Bhattacharjee , Flavio Seno

Scale-free dynamics, formalized by selfsimilarity, provides a versatile paradigm massively and ubiquitously used to model temporal dynamics in real-world data. However, its practical use has mostly remained univariate so far. By contrast,…

Methodology · Statistics 2024-04-04 Charles-Gérard Lucas , Gustavo Didier , Herwig Wendt , Patrice Abry

It is demonstrated how dynamic storage allocation algorithms can be analyzed in terms of finite size scaling. The method is illustrated in the three simple cases of the it first-fit, next-fit and it best-fit algorithms, and the system works…

Statistical Mechanics · Physics 2007-05-23 Hamed Seyed-allaei

Monte-Carlo simulations are routinely used for estimating the scaling exponents of complex systems. However, due to finite-size effects, determining the exponent values is often difficult and not reliable. Here we present a novel technique…

Computational Physics · Physics 2008-04-14 Jaan Kalda

Aligning theoretical atomistic structural models of materials with available experimental data presents a significant challenge for disordered systems. The configurational space to navigate is vast, and faithful realizations require large…

Materials Science · Physics 2025-09-29 Tigany Zarrouk , Miguel A. Caro

We revisit a simple dynamical model of rupture in random media with long-range elasticity to test whether rupture can be seen as a first-order or a critical transition. We find a clear scaling of the macroscopic modulus as a function of…

Statistical Mechanics · Physics 2009-10-30 D. Sornette , J. V. Andersen

Energy eigenvalues and order parameters are calculated by exact diagonalization for the transverse Ising model on square lattices of up to 6x6 sites. Finite-size scaling is used to estimate the critical parameters of the model, confirming…

Statistical Mechanics · Physics 2008-11-26 C. J. Hamer

This chapter covers methodological issues related to estimation, testing and computation for models involving structural changes. Our aim is to review developments as they relate to econometric applications based on linear models.…

Econometrics · Economics 2018-05-11 Alessandro Casini , Pierre Perron

Multidimensional scaling (MDS) is a popular dimensionality reduction techniques that has been widely used for network visualization and cooperative localization. However, the traditional stress minimization formulation of MDS necessitates…

Optimization and Control · Mathematics 2016-12-22 Ketan Rajawat , Sandeep Kumar

Measurement system analysis aims to quantify the variability in data attributable to the measurement system and evaluate its contribution to overall data variability. This paper conducts a rigorous theoretical investigation of the…

Applications · Statistics 2025-01-31 Banafsheh Lashkari , Shojaeddin Chenouri

We present large scale simulations of a stochastic sandpile model in two dimensions. We use moments analysis to evaluate critical exponents and finite size scaling method to consistently test the obtained results. The general picture…

Statistical Mechanics · Physics 2009-10-31 Alessandro Chessa , Alessandro Vespignani , Stefano Zapperi

Explicit time integration schemes coupled with Galerkin discretizations of time-dependent partial differential equations require solving a linear system with the mass matrix at each time step. For applications in structural dynamics, the…

Numerical Analysis · Mathematics 2024-03-15 Yannis Voet , Espen Sande , Annalisa Buffa

In this paper we investigate the question of how much combined measurements can increase the accuracy of additive quantities. Therefore, we consider a set of measurements from a selection of all possible combinations of the $n$ labeled…

Data Analysis, Statistics and Probability · Physics 2022-05-18 B. Mirbach , M. Boguslawski

Agile methodologies are used for improving productivity and quality of development originally created for small teams. However , now they are expanding to larger organizations, for which "scaled up" approaches have been proposed. This study…

Software Engineering · Computer Science 2020-12-22 Dilshat Salikhov , Giancarlo Succi , Alexander Tormasov

One of the most effective techniques of experimental mathematics is to compute mathematical entities such as integrals, series or limits to high precision, then attempt to recognize the resulting numerical values. Recently these techniques…

Mathematical Physics · Physics 2018-05-03 David H. Bailey , Jonathan M. Borwein , David Broadhurst , Wadim Zudilin