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A posteriori error estimator is derived for an elliptic interface problem in the fictitious domain formulation with distributed Lagrange multiplier considering a discontinuous Lagrange multiplier finite element space. A posteriori error…

Numerical Analysis · Mathematics 2024-07-02 Najwa Alshehri , Daniele Boffi , Lucia Gastaldi

Verification of software systems is a very hard problem due to the large size of program state-space. The traditional techniques (like model checking) do not scale; since they include the whole state-space by inlining the library function…

Logic in Computer Science · Computer Science 2010-05-03 Pritam Roy

Metric learning aims to learn a distance metric such that semantically similar instances are pulled together while dissimilar instances are pushed away. Many existing methods consider maximizing or at least constraining a distance margin in…

Machine Learning · Statistics 2022-08-17 Xiaochen Yang , Yiwen Guo , Mingzhi Dong , Jing-Hao Xue

In many iterative optimization methods, fixed-point theory enables the analysis of the convergence rate via the contraction factor associated with the linear approximation of the fixed-point operator. While this factor characterizes the…

Systems and Control · Electrical Eng. & Systems 2022-06-22 Trung Vu , Raviv Raich

This article presents a multi-physics methodology for the numerical simulation of physical systems that involve the non-linear interaction of multi-phase reactive fluids and elastoplastic solids, inducing high strain-rates and high…

Computational Physics · Physics 2021-06-04 Tim Wallis , Philip T. Barton , Nikolaos Nikiforakis

Interval arithmetic is a simple way to compute a mathematical expression to an arbitrary accuracy, widely used for verifying floating-point computations. Yet this simplicity belies challenges. Some inputs violate preconditions or cause…

Numerical Analysis · Mathematics 2021-07-14 Oliver Flatt , Pavel Panchekha

We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables to directly compare different atomic environments with an arbitrary number of…

Materials Science · Physics 2015-09-30 Gregoire Ferre , Jean-Bernard Maillet , Gabriel Stoltz

Software is now ubiquitous and involved in complex interactions with the human users and the physical world in so-called cyber-physical systems where the management of time is a major issue. Separation of concerns is a key asset in the…

Logic in Computer Science · Computer Science 2018-10-24 Mathieu Montin , Marc Pantel

Long linear polymers in a depinned interfaces environment have been studied for a long time, for instance in \cite{Caravenna2009depinning} when the temperature is constant. In this paper, we study an extension of this model by making the…

Probability · Mathematics 2024-10-10 Angot Elric

Contract-based design is a promising methodology for taming the complexity of developing sophisticated systems. A formal contract distinguishes between assumptions, which are constraints that the designer of a component puts on the…

Formal Languages and Automata Theory · Computer Science 2020-05-11 Ezio Bartocci , Thomas Ferrère , Thomas A. Henzinger , Dejan Nickovic , Ana Oliveira da Costa

Iterative refinement -- start with a random guess, then iteratively improve the guess -- is a useful paradigm for representation learning because it offers a way to break symmetries among equally plausible explanations for the data. This…

Machine Learning · Computer Science 2023-01-03 Michael Chang , Thomas L. Griffiths , Sergey Levine

Given a complex system with a given interface to the rest of the world, what does it mean for a the system to behave close to a simpler specification describing the behavior at the interface? We give several definitions for useful notions…

Optimization and Control · Mathematics 2021-11-25 Frank Hellmann , Ekaterina Zolotarevskaia , Jürgen Kurths , Jörg Raisch

Common measures of neural representational (dis)similarity are designed to be insensitive to rotations and reflections of the neural activation space. Motivated by the premise that the tuning of individual units may be important, there has…

Machine Learning · Computer Science 2023-11-17 Meenakshi Khosla , Alex H. Williams

The exact computation of the matching distance for multi-parameter persistence modules is an active area of research in computational topology. Achieving an easily obtainable exact computation of this distance would permit multi-parameter…

Algebraic Topology · Mathematics 2025-10-22 Asilata Bapat , Robyn Brooks , Celia Hacker , Claudia Landi , Barbara I. Mahler , Elizabeth R. Stephenson

Imbibition phenomena have been widely used experimentally and theoretically to study the kinetic roughening of interfaces. We critically discuss the existing experiments and some associated theoretical approaches on the scaling properties…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Dube , M. Rost , M. Alava

We introduce skipping refinement, a new notion of correctness for reasoning about optimized reactive systems. Reasoning about reactive systems using refinement involves defining an abstract, high-level specification system and a concrete,…

Logic in Computer Science · Computer Science 2015-02-11 Mitesh Jain , Panagiotis Manolios

Quality-sensitive applications of machine learning (ML) require quality assurance (QA) by humans before the predictions of an ML model can be deployed. QA for ML (QA4ML) interfaces require users to view a large amount of data and perform…

Human-Computer Interaction · Computer Science 2023-09-01 Yu Zhang , Martijn Tennekes , Tim de Jong , Lyana Curier , Bob Coecke , Min Chen

Roughening of interfaces implies the divergence of the interface width $w$ with the system size $L$. For two-dimensional systems the divergence of $w^2$ is linear in $L$. In the framework of a detailed capillary wave approximation and of…

Statistical Mechanics · Physics 2021-03-16 Gernot Münster , Manuel Cañizares Guerrero

The dynamics of sharp interfaces separating two non-hydrostatically stressed solids is analyzed using the idea that the rate of mass transport across the interface is proportional to the thermodynamic potential difference across the…

Materials Science · Physics 2009-11-13 Luiza Angheluta , Espen Jettestuen , Joachim Mathiesen

Classical machine learning approaches are sensitive to non-stationarity. Transfer learning can address non-stationarity by sharing knowledge from one system to another, however, in areas like machine prognostics and defense, data is…

Machine Learning · Computer Science 2022-09-07 Tyler Cody , Stephen Adams , Peter A. Beling