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We present a comprehensive pedagogical discussion of a family of models describing the propagation of a single particle in a multicomponent non-Markovian Gaussian random field. We report some exact results for single-particle Green's…

Mesoscale and Nanoscale Physics · Physics 2026-01-29 D. V. Efremov , M. N. Kiselev

In this paper we construct numerical schemes to approximate linear transport equations with slab geometry by diffusion equations. We treat both the case of pure diffusive scaling and the case where kinetic and diffusive scalings coexist.…

Numerical Analysis · Mathematics 2015-05-18 Qin Li , Jianfeng Lu , Weiran Sun

We propose a simple subsampling scheme for fast randomized approximate computation of optimal transport distances. This scheme operates on a random subset of the full data and can use any exact algorithm as a black-box back-end, including…

Computation · Statistics 2020-12-17 Max Sommerfeld , Jörn Schrieber , Yoav Zemel , Axel Munk

Deep-learning-based data-driven forecasting methods have produced impressive results for traffic forecasting. A major limitation of these methods, however, is that they provide forecasts without estimates of uncertainty, which are critical…

Machine Learning · Computer Science 2022-04-07 Tanwi Mallick , Prasanna Balaprakash , Jane Macfarlane

We study three classes of continuous time Markov processes (inclusion process, exclusion process, independent walkers) and a family of interacting diffusions (Brownian energy process). For each model we define a boundary driven process…

Mathematical Physics · Physics 2015-06-12 Gioia Carinci , Cristian Giardina' , Claudio Giberti , Frank Redig

We introduce a persistent random walk model with finite velocity and self-reinforcing directionality, which explains how exponentially distributed runs self-organize into truncated L\'evy walks observed in active intracellular transport by…

Statistical Mechanics · Physics 2024-02-07 Daniel Han , Marco A. A. da Silva , Nickolay Korabel , Sergei Fedotov

Random processes play a crucial role in scientific research, often characterized by distribution functions or probability density functions (PDFs). These PDFs serve as essential approximations of the actual and frequently undisclosed…

Methodology · Statistics 2023-06-06 Nico Schick

Rapid transit of emergency vehicles is critical for saving lives and reducing property loss but often relies on surrounding ordinary vehicles to cooperatively adjust their driving behaviors. It is important to ensure rapid transit of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 WenXi Wang , JunQi Zhang

We investigate confined L\'{e}vy flights under premises of the principle of detailed balance. The master equation admits a transformation to L\'{e}vy - Schr\"{o}dinger semigroup dynamics (akin to a mapping of the Fokker-Planck equation into…

Statistical Mechanics · Physics 2015-05-28 Piotr Garbaczewski , Vladimir Stephanovich

We study specific properties of particles transport by exploring an exact solvable model, a so-called comb structure, where diffusive transport of particles leads to subdiffusion. A performance of L\'evy -- like process enriches this…

Disordered Systems and Neural Networks · Physics 2007-05-23 E. Baskin , A. Iomin

We introduce a new approach to model and analyze \emph{Mobility}. It is fully based on discrete mathematics and yields a class of mobility models, called the \emph{Markov Trace} Model. This model can be seen as the discrete version of the…

Discrete Mathematics · Computer Science 2010-02-05 Andrea Clementi , Angelo Monti , Riccardo Silvestri

The ecological transition and the reduction of pollution are reasons for the use of green logistic and non-polluting vehicles. In this sense, electric vehicles are an alternative and in recent years many technological advances have been…

Optimization and Control · Mathematics 2021-11-02 Laura Antón , Marina Leal , José Luis Sainz-Pardo

The Software-Defined Air-Ground integrated Vehicular (SD-AGV) networks have emerged as a promising paradigm, which realize the flexible on-ground resource sharing to support innovative applications for UAVs with heavy computational…

Signal Processing · Electrical Eng. & Systems 2022-05-10 Minghui LiWang , Zhibin Gao , Xianbin Wang

The growing demand for electric vehicle (EV) charging infrastructure presents significant planning challenges, requiring efficient strategies for investment and operation to deliver cost-effective charging services. However, the potential…

Systems and Control · Electrical Eng. & Systems 2025-11-25 Xinda Zheng , Canchen Jiang , Hao Wang

We propose an effective explicit numerical scheme for simulating solutions of stochastic differential equations with confining superlinear drift terms, driven by multiplicative heavy-tailed L\'evy noise. The scheme is designed to prevent…

Computational Physics · Physics 2026-01-21 Ilya Pavlyukevich , Olga Aryasova , Alexei Chechkin , Oleksii Kulyk

Microscopic traffic simulation provides a controllable, repeatable, and efficient testing environment for autonomous vehicles (AVs). To evaluate AVs' safety performance unbiasedly, the probability distributions of environment statistics in…

Systems and Control · Electrical Eng. & Systems 2022-07-05 Xintao Yan , Shuo Feng , Haowei Sun , Henry X. Liu

The increasing penetration of electric vehicles (EVs) can provide substantial electricity to the grid, supporting the grids' stability. The state space model (SSM) has been proposed as an effective modeling method for power prediction and…

Systems and Control · Electrical Eng. & Systems 2025-03-07 Yiping Liu , Xiaozhe Wang , Geza Joos

We investigate the existence of weak type solutions for a class of aggregation-diffusion PDEs with nonlinear mobility obtained as large particle limit of a suitable nonlocal version of the follow-the-leader scheme, which is interpreted as…

Analysis of PDEs · Mathematics 2018-03-30 Simone Fagioli , Emanuela Radici

We consider so-called branched transport and variants thereof in two space dimensions. In these models one seeks an optimal transportation network for a given mass transportation task. In two space dimensions, they are closely connected to…

Numerical Analysis · Mathematics 2020-04-01 Carolin Dirks , Benedikt Wirth

A probability distribution allows practitioners to uncover hidden structure in the data and build models to solve supervised learning problems using limited data. The focus of this report is on Variational autoencoders, a method to learn…

Machine Learning · Computer Science 2022-06-22 Vasanth Kalingeri