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Model checking is usually based on a comprehensive traversal of the state space. Causality-based model checking is a radically different approach that instead analyzes the cause-effect relationships in a program. We give an overview on a…

Logic in Computer Science · Computer Science 2017-10-11 Bernd Finkbeiner , Andrey Kupriyanov

A formalism is derived to analyze the scattering of a conducting structure based on the characteristic modes of another structure whose surface is a superset of the first structure. This enables the analysis and comparison of different…

Signal Processing · Electrical Eng. & Systems 2025-12-10 Leonardo Mörlein , Dirk Manteuffel

Recent control trends are increasingly relying on communication networks and wireless channels to close the loop for Internet-of-Things applications. Traditionally these approaches are model-based, i.e., assuming a network or channel model…

Systems and Control · Electrical Eng. & Systems 2019-11-11 Konstantinos Gatsis , George J. Pappas

Scattering resonances arise in wave phenomena and play an important role in many applications. While extensive theoretical studies have been conducted, effective numerical computation remains limited, and most existing methods suffer from…

Numerical Analysis · Mathematics 2026-04-17 Bo Gong , Jiguang Sun

The wavelet scattering transform creates geometric invariants and deformation stability. In multiple signal domains, it has been shown to yield more discriminative representations compared to other non-learned representations and to…

The scattering matrix was measured for a flat microwave cavity with classically chaotic dynamics. The system can be perturbed by small changes of the geometry. We define the "scattering fidelity" in terms of parametric correlation functions…

Chaotic Dynamics · Physics 2009-11-10 R. Schaefer , T. Gorin , T. H. Seligman , H. -J. Stoeckmann

Fault-tolerant distributed algorithms are central for building reliable spatially distributed systems. Unfortunately, the lack of a canonical precise framework for fault-tolerant algorithms is an obstacle for both verification and…

Formal Languages and Automata Theory · Computer Science 2012-10-16 Annu John , Igor Konnov , Ulrich Schmid , Helmut Veith , Josef Widder

In 2D acoustic and elastodynamic problems the spatial variability of a constitutive parameter such as the mass density makes it difficult to employ boundary integral and domain integral techniques to solve the forward and inverse wave…

Geophysics · Physics 2019-03-25 Armand Wirgin

Feature selection is an important but challenging task in causal inference for obtaining unbiased estimates of causal quantities. Properly selected features in causal inference not only significantly reduce the time required to implement a…

Methodology · Statistics 2025-02-04 Tianyu Yang , Md. Noor-E-Alam

Non-deterministically behaving (i.e., flaky) tests hamper regression testing as they destroy trust and waste computational and human resources. Eradicating flakiness in test suites is therefore an important goal, but automated debugging…

Software Engineering · Computer Science 2023-05-09 Martin Gruber , Gordon Fraser

Root cause analysis of anomalies aims to identify how and why a sample deviates from the normal process. Existing methods primarily focus on telling which features are responsible, ignoring that anomalies can arise through two fundamentally…

Machine Learning · Computer Science 2026-05-12 Hendrik Suhr , David Kaltenpoth , Jilles Vreeken

We present a quantitative study of coherent array imaging of remote sources in randomly perturbed waveguides with bounded cross-section. We study how long range cumulative scattering by perturbations of the boundary and the medium impedes…

Numerical Analysis · Mathematics 2013-06-10 Liliana Borcea , Josselin Garnier , Chrysoula Tsogka

A data analysis pipeline is a structured sequence of steps that transforms raw data into meaningful insights by integrating various analysis algorithms. In this paper, we propose a novel statistical test to assess the significance of data…

Machine Learning · Statistics 2024-10-15 Tomohiro Shiraishi , Tatsuya Matsukawa , Shuichi Nishino , Ichiro Takeuchi

Imputation methods play a critical role in enhancing the quality of practical time-series data, which often suffer from pervasive missing values. Recently, diffusion-based generative imputation methods have demonstrated remarkable success…

Machine Learning · Computer Science 2025-10-03 Zeqi Ye , Minshuo Chen

A method for automatic computation of parameter derivatives of numerically computed light scattering signals is demonstrated. The finite-element based method is validated in a numerical convergence study, and it is applied to investigate…

Optics · Physics 2013-04-17 S. Burger , L. Zschiedrich , J. Pomplun , F. Schmidt , B. Bodermann

We introduce an approach which allows detecting causal relationships between variables for which the time evolution is available. Causality is assessed by a variational scheme based on the Information Imbalance of distance ranks, a…

Methodology · Statistics 2024-05-07 Vittorio Del Tatto , Gianfranco Fortunato , Domenica Bueti , Alessandro Laio

A multivariate score-driven filter is developed to extract signals from noisy vector processes. By assuming that the conditional location vector from a multivariate Student's t distribution changes over time, we construct a robust filter…

Econometrics · Economics 2022-08-31 Enzo D'Innocenzo , Alessandra Luati , Mario Mazzocchi

Resonant transmission occurs when constructive interference results in the complete passage of an incoming wave through an array of barriers. In this paper we explore such a scenario with one dimensional models. We adopt wave packets with…

Quantum Physics · Physics 2023-10-11 A. M. Michalik , F. Marsiglio

We propose a new approach to detailed balance violation in electrical circuits by relying on the scattering matrix formalism commonly used in microwave electronics. This allows to include retardation effects which are paramount at high…

Mesoscale and Nanoscale Physics · Physics 2024-03-27 Alexandre Dumont , Pierre Février , Christian Lupien , Bertrand Reulet

In prior work we have introduced an asymptotic threshold of sufficient randomness for causal inference from observational data. In this paper we extend that prior work in three main ways. First, we show how to empirically estimate a lower…

Methodology · Statistics 2023-09-07 Brian Knaeble , Braxton Osting , Placede Tshiaba