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In this work, we consider an advection-diffusion equation, coupled to a Poisson equation for the velocity field. This type of coupling is typically encountered in models arising from plasma physics or porous media flow. The aim of this work…

Numerical Analysis · Mathematics 2023-02-14 Hanz Martin Cheng , Jan ten Thije Boonkkamp

Subsurface flows are commonly modeled by advection-diffusion equations. Insufficient measurements or uncertain material procurement may be accounted for by random coefficients. To represent, for example, transitions in heterogeneous media,…

Numerical Analysis · Mathematics 2021-01-25 Andrea Barth , Andreas Stein

In this study, a novel semi-implicit second-order temporal scheme combined with the finite element method for space discretization is proposed to solve the coupled system of infiltration and solute transport in unsaturated porous media. The…

Numerical Analysis · Mathematics 2024-06-11 Nour-eddine Toutlini , Abdelaziz Beljadid , Azzeddine Soulaïmani

This paper presents a new deformable convolution-based video frame interpolation (VFI) method, using a coarse to fine 3D CNN to enhance the multi-flow prediction. This model first extracts spatio-temporal features at multiple scales using a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Duolikun Danier , Fan Zhang , David Bull

Visual repetition is ubiquitous in our world. It appears in human activity (sports, cooking), animal behavior (a bee's waggle dance), natural phenomena (leaves in the wind) and in urban environments (flashing lights). Estimating visual…

Computer Vision and Pattern Recognition · Computer Science 2018-06-20 Tom F. H. Runia , Cees G. M. Snoek , Arnold W. M. Smeulders

Generative models have emerged as a powerful paradigm for solving physics systems and modeling complex spatiotemporal dynamics. However, achieving high physical accuracy without incurring high computational cost remains a fundamental…

Machine Learning · Computer Science 2026-05-27 Jiahe Huang , Sihan Xu , Sharvaree Vadgama , Rose Yu

We investigate the reconstruction of a turbulent flow field in the atmospheric boundary layer from a time series of lidar measurements, using Large-Eddy Simulations (LES) and a 4D-Var data assimilation algorithm. This leads to an…

Fluid Dynamics · Physics 2020-11-17 Pieter Bauweraerts , Johan Meyers

This study addresses the critical challenge of error accumulation in spatio-temporal auto-regressive (AR) predictions within scientific machine learning models by exploring temporal integration schemes and adaptive multi-step rollout…

Machine Learning · Computer Science 2025-09-25 Sunwoong Yang , Ricardo Vinuesa , Namwoo Kang

We propose a procedure for the determination of the time-dependent velocity and pressure fields of an unbounded incompressible viscous fluid in an external force field induced by an arbitrary number of spheres moving and rotating in it as…

Fluid Dynamics · Physics 2007-05-23 A. S. Usenko

The volume-filtering of the Navier-Stokes equations allows to consider the effect that particles have on the fluid without further assumptions, but closures arise of which the implications are not fully understood. In the present paper, we…

Fluid Dynamics · Physics 2024-11-20 Max Hausmann , Victor Chéron , Fabien Evrard , Berend van Wachem

This paper deals with determination of turbulent convection velocities from particle image velocimetry (PIV). Turbulent convection velocities are of interest because they can be used to map temporal information into space. Convection…

Fluid Dynamics · Physics 2013-11-26 Roeland de Kat , Lian Gan , James R Dawson , Bharathram Ganapathisubramani

In this paper, four distinct approaches to Volume of Fluid (VOF) computational method are compared. Two of the methods are the 'simplified' VOF formulations, in that they do not require geometrical interface reconstruction. The assessment…

Computational Physics · Physics 2014-05-21 Wojciech Aniszewski , Thibaut Ménard , Maciej Marek

Bayesian full waveform inversion (FWI) offers uncertainty-aware subsurface models; however, posterior sampling directly on observed seismic shot records is rarely practical at the field scale because each sample requires numerous…

Geophysics · Physics 2025-12-16 Mohammad H. Taufik , Tariq Alkhalifah

Within the scope of this contribution we propose a novel efficient spatio-temporal prediction algorithm for video coding. The algorithm operates in two stages. First, motion compensation is performed on the block to be predicted in order to…

Image and Video Processing · Electrical Eng. & Systems 2022-07-21 Jürgen Seiler , Haricharan Lakshman , André Kaup

Atmospheric trace-gas inversion refers to any technique used to predict spatial and temporal fluxes using mole-fraction measurements and atmospheric simulations obtained from computer models. Studies to date are most often of a…

We propose a new variational model for joint image reconstruction and motion estimation in spatiotemporal imaging, which is investigated along a general framework that we present with shape theory. This model consists of two components, one…

Numerical Analysis · Mathematics 2019-11-06 Chong Chen , Barbara Gris , Ozan Öktem

Multi-step prediction models, such as diffusion and rectified flow models, have emerged as state-of-the-art solutions for generation tasks. However, these models exhibit higher latency in sampling new frames compared to single-step methods.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Gaurav Shrivastava , Abhinav Shrivastava

This paper is concerned with the inverse problem of time-harmonic acoustic scattering by an unbounded, locally rough interface which is assumed to be a local perturbation of a plane. The purpose of this paper is to recover the local…

Analysis of PDEs · Mathematics 2020-08-05 Jianliang Li , Jiaqing Yang , Bo Zhang

Diffusion model (DM)-based channel estimation, which generates channel samples via a posteriori sampling stepwise with denoising process, has shown potential in high-precision channel state information (CSI) acquisition. However, slow…

Machine Learning · Computer Science 2025-11-17 Wenkai Liu , Nan Ma , Jianqiao Chen , Xiaoxuan Qi , Yuhang Ma

We consider the problem of state estimation in dynamical systems and propose a different mechanism for handling unmodeled system uncertainties. Instead of injecting random process noise, we assign different weights to measurements so that…

Information Theory · Computer Science 2020-09-08 Yaron Shulami , Daniel Sigalov
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