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Gaussian Process state-space models capture complex temporal dependencies in a principled manner by placing a Gaussian Process prior on the transition function. These models have a natural interpretation as discretized stochastic…

Machine Learning · Computer Science 2022-02-24 Krista Longi , Jakob Lindinger , Olaf Duennbier , Melih Kandemir , Arto Klami , Barbara Rakitsch

The assignment problem, a cornerstone of operations research, seeks an optimal one-to-one mapping between agents and tasks to minimize total cost. This work traces its evolution from classical formulations and algorithms to modern optimal…

Optimization and Control · Mathematics 2025-09-05 Iman Seyedi , Antonio Candelieri , Enza Messina , Francesco Archetti

Traffic flow forecasting is of great significance for improving the efficiency of transportation systems and preventing emergencies. Due to the highly non-linearity and intricate evolutionary patterns of short-term and long-term traffic…

Machine Learning · Computer Science 2020-12-01 Xu Chen , Yuanxing Zhang , Lun Du , Zheng Fang , Yi Ren , Kaigui Bian , Kunqing Xie

The key to traffic prediction is to accurately depict the temporal dynamics of traffic flow traveling in a road network, so it is important to model the spatial dependence of the road network. The essence of spatial dependence is to…

Machine Learning · Computer Science 2023-06-28 Silu He , Qinyao Luo , Ronghua Du , Ling Zhao , Haifeng Li

Accurately forecasting bus travel time and passenger occupancy with uncertainty is essential for both travelers and transit agencies/operators. However, existing approaches to forecasting bus travel time and passenger occupancy mainly rely…

Applications · Statistics 2024-12-12 Xiaoxu Chen , Zhanhong Cheng , Alexandra M. Schmidt , Lijun Sun

We present and analyze a discontinuous Galerkin method for the numerical modelling of the non-linear fully-coupled thermo-poroelastic problem. For the spatial discretization, we design a high-order discontinuous Galerkin method on polygonal…

Numerical Analysis · Mathematics 2022-05-27 Paola F. Antonietti , Stefano Bonetti , Michele Botti

Time-slicing has emerged as a strategy for incorporating semiclassical propagation into real-time path integral formulation and recovering full quantum dynamics. A central step is the decomposition of a time-evolved wave function into a…

Quantum Physics · Physics 2026-03-13 Rahul Sharma , Amartya Bose

We put forward a gauge-invariant theoretical framework for studying time-resolved thermoelectric transport in an arbitrary multiterminal electronic quantum system described by a non-interacting tight-binding model. The system is driven out…

Mesoscale and Nanoscale Physics · Physics 2020-06-18 Adel Kara Slimane , Phillipp Reck , Geneviève Fleury

A Gaussian operator basis provides a means to formulate phase-space simulations of the real- and imaginary-time evolution of quantum systems. Such simulations are guaranteed to be exact while the underlying distribution remains…

Computational Physics · Physics 2012-04-04 M. Ogren , K. V. Kheruntsyan , J. F. Corney

We derive quantum Boltzmann equations from Schwinger-Dyson equations in gradient expansion for a weakly coupled scalar field theory with a spatially varying mass. We find that at higher order in gradients a full description of the system…

High Energy Physics - Phenomenology · Physics 2009-10-31 Michael Joyce , Kimmo Kainulainen , Tomislav Prokopec

We introduce the time-dependent ghost Gutzwiller approximation (td-gGA), a non-equilibrium extension of the ghost Gutzwiller approximation (gGA), a powerful variational approach which systematically improves on the standard Gutzwiller…

Strongly Correlated Electrons · Physics 2023-08-23 Daniele Guerci , Massimo Capone , Nicola Lanatà

We present the model of transit universe from early deceleration phase to current acceleration phase under the framework of general relativity in presence of gravitational coupling $G(t)$ and cosmological terms $\Lambda(t)$. The Einstein's…

General Physics · Physics 2015-06-11 Anil Kumar Yadav , A. Sharma

We investigate the transport properties of a kinetic theory model that is tuned to describe the thermodynamic properties of QCD at zero chemical potential using a new formulation of the relaxation time approximation. In contrast to previous…

Nuclear Theory · Physics 2022-08-24 Gabriel S. Rocha , Maurício N. Ferreira , Gabriel S. Denicol , Jorge Noronha

In this paper, we present a new space-time Petrov-Galerkin-like method. This method utilizes a mixed formulation of Tensor Train (TT) and Quantized Tensor Train (QTT), designed for the spectral element discretization (Q1-SEM) of the…

Quantum transport in a narrow constriction, and in the presence of a finite-range time-modulated potential, is studied. The potential is taken the form $V(x,t) = V_{0} \theta(x)\theta(a-x)\cos(\omega t)$, with $a$ the range of the potential…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 C. S. Tang , C. S. Chu

We develop a new framework for branched transport between probability measures which are allowed to vary in time. This framework can be used to model problems where the underlying transportation network displays a branched structure, but…

Optimization and Control · Mathematics 2025-12-25 Jun Kitagawa , Cecilia Mikat

We apply the collision-based hybrid introduced in \cite{hauck} to the Boltzmann equation with the BGK operator and a hyperbolic scaling. An implicit treatment of the source term is used to handle stiffness associated with the BGK operator.…

Numerical Analysis · Mathematics 2023-06-21 Minwoo Shin , Cory D. Hauck , Ryan G. McClarren

The method of approximate automodel solution for the Green's function of the time-dependent superdiffusive (nonlocal) transport equations (J. Phys. A: Math. Theor. 49 (2016) 255002) is extended to the case of a finite velocity of carriers.…

Statistical Mechanics · Physics 2019-09-04 A. B. Kukushkin , A. A. Kulichenko

Stochastic transport due to a velocity field modeled by the superposition of small-scale divergence free vector fields activated by Fractional Gaussian Noises (FGN) is numerically investigated. We present two non-trivial contributions: the…

Statistical Mechanics · Physics 2025-06-12 Paolo Cifani , Franco Flandoli

We develop a dynamic generalized conditional gradient method (DGCG) for dynamic inverse problems with optimal transport regularization. We consider the framework introduced in (Bredies and Fanzon, ESAIM: M2AN, 54:2351-2382, 2020), where the…

Numerical Analysis · Mathematics 2023-08-16 Kristian Bredies , Marcello Carioni , Silvio Fanzon , Francisco Romero