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Purpose: To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water-fat imaging and flow imaging. Theory and Methods: The problem of enforcing phase constraints in reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2017-09-26 Frank Ong , Joseph Cheng , Michael Lustig

A novel mathematical model for fiber-reinforced materials is proposed. It is based on a 1-dimensional beam model for the thin fiber structures, a flexible and general 3-dimensional elasticity model for the matrix and an overlapping domain…

Computational Engineering, Finance, and Science · Computer Science 2021-05-12 Ustim Khristenko , Stefan Schuß , Melanie Krüger , Felix Schmidt , Barbara Wohlmuth , Christian Hesch

In this letter, we develop a continuous fluid antenna (FA) framework for uplink channel estimation in cell-free massive multiple-input and multiple-output (CF-mMIMO) systems. By modeling the wireless channel as a spatially correlated…

Information Theory · Computer Science 2026-02-19 Masoud Kaveh , Farshad Rostami Ghadi , Francisco Hernando-Gallego , Diego Martin , Riku Jantti , Kai-Kit Wong

An analytical soluble model based on a Continuous Time Random Walk (CTRW) scheme for the adsorption-desorption processes at interfaces, called bulk-mediated surface diffusion, is presented. The time evolution of the effective probability…

Condensed Matter · Physics 2009-11-10 Jorge A. Revelli , Carlos. E. Budde , Domingo Prato , Horacio S. Wio

We introduce a new paradigm for generative modeling built on Continuous Normalizing Flows (CNFs), allowing us to train CNFs at unprecedented scale. Specifically, we present the notion of Flow Matching (FM), a simulation-free approach for…

Machine Learning · Computer Science 2023-02-09 Yaron Lipman , Ricky T. Q. Chen , Heli Ben-Hamu , Maximilian Nickel , Matt Le

Hybrid methods for simulating rarefied gas flows reduce computational cost by coupling a particle-based model, typically the direct simulation Monte Carlo (DSMC) method, to a continuum-based solver, i.e. a computational fluid dynamics (CFD)…

Fluid Dynamics · Physics 2026-04-28 Arshad Kamal , Arun K. Chinnappan , James R. Kermode , Duncan A. Lockerby

Multi-objective embedding-based retrieval (EBR) has become increasingly critical due to the growing complexity of user behaviors and commercial objectives. While traditional approaches often suffer from data sparsity and limited information…

Information Retrieval · Computer Science 2025-04-18 Hao Deng , Haibo Xing , Kanefumi Matsuyama , Moyu Zhang , Jinxin Hu , Hong Wen , Yu Zhang , Xiaoyi Zeng , Jing Zhang

The properties of polymer liquids on hard and soft substrates are investigated by molecular dynamics simulation of a coarse-grained bead-spring model and dynamic single-chain-in-mean-field (SCMF) simulations of a soft, coarse-grained…

Soft Condensed Matter · Physics 2015-05-18 F. Léonforte , J. Servantie , C. Pastorino , M. Müller

Continuous Normalizing Flows (CNFs) enable elegant generative modeling but remain bottlenecked by slow sampling: producing a single sample requires solving a nonlinear ODE with hundreds of function evaluations. Recent approaches such as…

Machine Learning · Computer Science 2025-10-23 Erkan Turan , Aristotelis Siozopoulos , Louis Martinez , Julien Gaubil , Emery Pierson , Maks Ovsjanikov

In order to prevent velocity, pressure, and temperature spikes at material discontinuities occurring when the interface-capturing schemes inconsistently simulate compressible multi-material flows(when the specific heats ratio is…

Computational Physics · Physics 2020-12-29 Zhiwei He , Yousheng Zhang , Li Li , Baolin Tian

Continuous normalizing flows (CNFs) learn an ordinary differential equation to transform prior samples into data. Flow matching (FM) has recently emerged as a simulation-free approach for training CNFs by regressing a velocity model towards…

Machine Learning · Statistics 2024-05-28 Tianyu Xie , Yu Zhu , Longlin Yu , Tong Yang , Ziheng Cheng , Shiyue Zhang , Xiangyu Zhang , Cheng Zhang

The source distribution in conditional flow matching is a design parameter that can be calibrated to data, not a default isotropic prior. We exploit this in Multi-Fidelity Flow Matching (MFFM), a cascade refinement framework for parametric…

Machine Learning · Computer Science 2026-05-18 Sipeng Chen , Junliang Liu , Hewei Tang , Shibo Li

Conditional particle filters (CPFs) are powerful smoothing algorithms for general nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult to apply with diffuse initial distributions, which are common in…

Computation · Statistics 2020-11-23 Santeri Karppinen , Matti Vihola

Diffuse-interface theory provides a foundation for the modeling and simulation of microstructure evolution in a very wide range of materials, and for the tracking/capturing of dynamic interfaces between different materials on larger scales.…

Computational Physics · Physics 2018-08-03 Zhijie Xu , Paul Meakin , Alexandre Tartakovsky

The use of CT imaging is important for screening, diagnosis, therapy planning, and prognosis of lung cancers. Unfortunately, due to differences in imaging protocols and scanner models, CT images acquired by different means may show large…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Md Shifatul Ahsan Apurba , Md Selim , Jin Chen

The present work introduces a novel numerical approach for the process modeling of fiber-reinforced thermoset polymers at the micro-scale level, that can be used to predict curing-induced residual stresses. The cure kinetics is described…

Applied Physics · Physics 2022-12-14 Manish H. Nagaraj , Marianna Maiaru

It has been known for long that the fluctuation surface tension of membranes $r$, computed from the height fluctuation spectrum, is not equal to the bare surface tension $\sigma$ introduced in the Helfrich theory. In this work we relate…

Soft Condensed Matter · Physics 2017-09-05 Guillaume Gueguen , Nicolas Destainville , Manoel Manghi

Smoothed particle hydrodynamics (SPH) has been extensively studied in computer graphics to animate fluids with versatile effects. However, SPH still suffers from two numerical difficulties: the particle deficiency problem, which will…

Graphics · Computer Science 2020-01-29 Xiaowei He , Huamin Wang , Guoping Wang , Hongan Wang , Enhua Wu

The aim of this work is to propose a provably convergent finite volume scheme for the so-called Stefan-Maxwell model, which describes the evolution of the composition of a multi-component mixture and reads as a cross-diffusion system. The…

Numerical Analysis · Mathematics 2020-07-21 Clément Cancès , Virginie Ehrlacher , Laurent Monasse

This work expands on our recently introduced low Mach enthalpy method [1] for simulating the melting and solidification of a phase change material (PCM) alongside (or without) an ambient gas phase. The method captures PCM's volume change…

Fluid Dynamics · Physics 2025-03-11 Ramakrishnan Thirumalaisamy , Amneet Pal Singh Bhalla