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During the past two decades there has been a lot of interest in developing statistical depth notions that generalize the univariate concept of ranking to multivariate data. The notion of depth has also been extended to regression models and…

Methodology · Statistics 2015-08-18 Peter J. Rousseeuw , Mia Hubert

Modelling river physical processes is of critical importance for flood protection, river management and restoration of riverine environments. Developments in algorithms and computational power have led to a wider spread of river simulation…

The Mat\'ern model has been a cornerstone of spatial statistics for more than half a century. More recently, the Mat\'ern model has been central to disciplines as diverse as numerical analysis, approximation theory, computational…

Statistics Theory · Mathematics 2023-03-07 Emilio Porcu , Moreno Bevilacqua , Robert Schaback , Chris J. Oates

Understanding how data quality aligns with regulatory requirements in machine learning (ML) systems presents a critical challenge for practitioners navigating the evolving EU regulatory landscape. To address this, we first propose a…

Databases · Computer Science 2026-02-09 Yichun Wang , Kristina Irion , Paul Groth , Hazar Harmouch

Research on methods for planning and controlling water distribution networks gains increasing relevance as the availability of drinking water will decrease as a consequence of climate change. So far, the majority of approaches is based on…

The use of statistical software in academia and enterprises has been evolving over the last years. More often than not, students, professors, workers, and users, in general, have all had, at some point, exposure to statistical software.…

Applications · Statistics 2019-08-21 Rui Portocarrero Sarmento , Vera Costa

A variety of computational models have been developed to describe active matter at different length and time scales. The diversity of the methods and the challenges in modeling active matter---ranging from molecular motors and cytoskeletal…

Soft Condensed Matter · Physics 2020-04-21 M Reza Shaebani , Adam Wysocki , Roland G Winkler , Gerhard Gompper , Heiko Rieger

We investigate two common numerical techniques for integrating reversible moist processes in atmospheric flows in the context of solving the fully compressible Euler equations. The first is a one-step, coupled technique based on using…

Atmospheric and Oceanic Physics · Physics 2015-05-11 Max Duarte , Ann S. Almgren , Kaushik Balakrishnan , John B. Bell , David M. Romps

The problem of mathematical modeling in geography is one of the most important strategies in order to establish the evolution and the prevision of geographical phenomena. Models must have a simplified structure, to reflect essential…

Computational Geometry · Computer Science 2012-03-06 Ionica Soare , Carmen Antohe

Ocean science is a discipline that employs ocean models as an essential research asset. Such scientific modeling provides mathematical abstractions of real-world systems, e.g., the oceans. These models are then coded as implementations of…

Software Engineering · Computer Science 2022-02-03 Reiner Jung , Sven Gundlach , Wilhelm Hasselbring

For several years, students visit us on different occasions at the university. But how to bridge from the school curriculum to the contents of the university mathematics? And how to find a focal point at which an active contribute, despite…

Optimization and Control · Mathematics 2016-03-26 Miriam Kießling , Sascha Kurz , Tobias Kreisel , Jörg Rambau , Konra Schade , Cornelius Schwarz

Environmental data science for spatial extremes has traditionally relied heavily on max-stable processes. Even though the popularity of these models has perhaps peaked with statisticians, they are still perceived and considered as the…

Methodology · Statistics 2024-02-01 Raphaël Huser , Thomas Opitz , Jennifer Wadsworth

Nowadays hydroelectric energy is one of the best energy sources: it is cleaner, safer and more programmable than other sources. For this reason, its manage could not be done in an approssimative way, but advance mathematical models must be…

Computational Engineering, Finance, and Science · Computer Science 2016-11-01 Matteo Gardini , Aurora Manicardi

In this paper, properties of a recently proposed mathematical model for data flow in large-scale asynchronous computer systems are analyzed. In particular, the existence of special weak solutions based on propagating fronts is established.…

Analysis of PDEs · Mathematics 2020-07-28 C. D. Hauck , M. Herty , G. Visconti

The article highlights the promising ways of providing access to the mathematical software in higher educational institutions. It is emphasized that the cloud computing services implementation is the actual trend of modern ICT pedagogical…

Computers and Society · Computer Science 2018-07-06 Mariya Shyshkina , Uliana Kohut , Maiia Popel

Currently, a variety of pipeline tools are available for use in data engineering. Data scientists can use these tools to resolve data wrangling issues associated with data and accomplish some data engineering tasks from data ingestion…

Machine Learning · Computer Science 2024-06-21 Anthony Mbata , Yaji Sripada , Mingjun Zhong

The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from field measurements, experiments and large-scale simulations at multiple spatiotemporal scales. Machine learning offers a wealth of techniques to…

Fluid Dynamics · Physics 2020-02-19 Steven Brunton , Bernd Noack , Petros Koumoutsakos

Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-preformed studies…

Software Engineering · Computer Science 2020-08-11 Yanming Yang , Xin Xia , David Lo , Tingting Bi , John Grundy , Xiaohu Yang

Data preparation, especially data cleaning, is very important to ensure data quality and to improve the output of automated decision systems. Since there is no single tool that covers all steps required, a combination of tools -- namely a…

Databases · Computer Science 2023-08-29 Valerie Restat

Signal processing, communications, and control have traditionally relied on classical statistical modeling techniques. Such model-based methods utilize mathematical formulations that represent the underlying physics, prior information and…

Signal Processing · Electrical Eng. & Systems 2022-09-13 Nir Shlezinger , Jay Whang , Yonina C. Eldar , Alexandros G. Dimakis