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In many tasks, in particular in natural science, the goal is to determine hidden system parameters from a set of measurements. Often, the forward process from parameter- to measurement-space is a well-defined function, whereas the inverse…

Predicting pedestrian motion trajectories is critical for the path planning and motion control of autonomous vehicles. Recent diffusion-based models have shown promising results in capturing the inherent stochasticity of pedestrian behavior…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Yu Liu , Zhijie Liu , Xiao Ren , You-Fu Li , He Kong

This paper considers the optimal sensor allocation for estimating the emission rates of multiple sources in a two-dimensional spatial domain. Locations of potential emission sources are known (e.g., factory stacks), and the number of…

Computation · Statistics 2025-09-09 Xinchao Liu , Dzung Phan , Youngdeok Hwang , Levente Klein , Xiao Liu , Kyongmin Yeo

The motion of self-propelled particles is modeled as a persistent random walk. An analytical framework is developed that allows the derivation of exact expressions for the time evolution of arbitrary moments of the persistent walk's…

Soft Condensed Matter · Physics 2015-07-28 Zeinab Sadjadi , M. Reza Shaebani , Heiko Rieger , Ludger Santen

With recent advances in sensing and tracking technology, trajectory data is becoming increasingly pervasive and analysis of trajectory data is becoming exceedingly important. A fundamental problem in analyzing trajectory data is that of…

Computational Geometry · Computer Science 2013-03-08 Swaminathan Sankararaman , Pankaj K. Agarwal , Thomas Mølhave , Arnold P. Boedihardjo

More than ten years ago Ikehata discovered two mathematical methods for the purpose of extracting information about the location and shape of unknown discontinuity embedded in a known background medium from observation data. The methods are…

Analysis of PDEs · Mathematics 2011-09-21 Masaru Ikehata

We consider the problem of goodness-of-fit testing for a model that has at least one unknown parameter that cannot be eliminated by transformation. Examples of such problems can be as simple as testing whether a sample consists of…

Methodology · Statistics 2021-04-28 Sean van der Merwe

Air pollution is a major global environmental health threat, in particular for people who live or work near pollution sources. Areas adjacent to pollution sources often have high ambient pollution concentrations, and those areas are…

Machine Learning · Computer Science 2022-11-16 Yawen Zhang , Michael Hannigan , Qin Lv

Waveform inversion is theoretically a powerful tool to reconstruct subsurface structures, but a usually encountered problem is that accurate sources are very rare, causing the computation unstable and divergent. This challenging problem,…

Geophysics · Physics 2024-07-12 Han Yu

Data-driven emulators are increasingly being used to learn and emulate physics-based simulations, reducing computational expense and run time. Here, we present a structured way to improve the quality of these high-dimensional emulated…

Machine Learning · Computer Science 2025-04-25 Nawid Keshtmand , Elena Fillola , Jeffrey Nicholas Clark , Raul Santos-Rodriguez , Matthew Rigby

This work provides a short clarification on the definition of specific interfacial areas in aerated flows, thereby distinguishing between the specific interfacial area related to the volume of an air-water mixture, and the specific…

Fluid Dynamics · Physics 2025-04-07 Matthias Kramer

Air pollution, especially particulate matter 2.5 (PM2.5), is a pressing concern for public health and is difficult to estimate in developing countries (data-poor regions) due to a lack of ground sensors. Transfer learning models can be…

Machine Learning · Computer Science 2024-06-25 Shrey Gupta , Yongbee Park , Jianzhao Bi , Suyash Gupta , Andreas Züfle , Avani Wildani , Yang Liu

Cloud computing offers an opportunity to run compute-resource intensive climate models at scale by parallelising model runs such that datasets useful to the exoplanet community can be produced efficiently. To better understand the…

Differential atmospheric dispersion is a wavelength-dependent effect introduced by Earth's atmosphere that affects astronomical observations performed using ground-based telescopes. It is important, when observing at a zenithal angle…

Instrumentation and Methods for Astrophysics · Physics 2021-03-17 B. Wehbe. , A. Cabral , L. Sbordone , G. Avila

In these lectures I give an introduction to the time-dependent approach to inverse scattering, that has been developed recently. The aim of this approach is to solve various inverse scattering problems with time-dependent methods that…

Mathematical Physics · Physics 2007-05-23 Ricardo Weder

Decision analysis deals with modeling and enhancing decision processes. A principal challenge in improving behavior is in obtaining a transparent description of existing behavior in the first place. In this paper, we develop an expressive,…

Machine Learning · Statistics 2023-10-31 Daniel Jarrett , Alihan Hüyük , Mihaela van der Schaar

Modern earthwork compaction rollers collect location and compaction information as they traverse a compaction site. These roller measurement values present a challenging spatio-temporal statistical problem that requires careful…

Applications · Statistics 2013-03-21 Daniel K. Heersink , Reinhard Furrer , Mike A. Mooney

Recurrence is a fundamental property of dynamical systems, which can be exploited to characterise the system's behaviour in phase space. A powerful tool for their visualisation and analysis called recurrence plot was introduced in the late…

Chaotic Dynamics · Physics 2025-01-27 Norbert Marwan , Maria Carmen Romano , Marco Thiel , Jürgen Kurths

This work investigates the scattering coefficients for inverse medium scattering problems. It shows some fundamental properties of the coefficients such as symmetry and tensorial properties. The relationship between the scattering…

Analysis of PDEs · Mathematics 2013-10-24 Habib Ammari , Yat Tin Chow , Jun Zou

This article introduces new methods for inference with count data registered on a set of aggregation units. Such data are omnipresent in epidemiology due to confidentiality issues: it is much more common to know the county in which an…

Methodology · Statistics 2017-04-20 Benjamin M. Taylor , Ricardo Andrade-Pacheco , Hugh J. W. Sturrock
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