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3D semantic scene completion and 2D semantic segmentation are two tightly correlated tasks that are both essential for indoor scene understanding, because they predict the same semantic classes, using positively correlated high-level…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Jie Li , Laiyan Ding , Rui Huang

We propose a concept of dissipative weak (DW) solutions for the Navier-Stokes-Korteweg (NSK) system and prove conditional convergence of a structure-preserving finite volume scheme towards such a solution. DW solutions provide a generalized…

Numerical Analysis · Mathematics 2026-04-20 Jan Giesselmann , Philipp Öffner , Robert Sauerborn

We study the equilibrium configurations of a possibly asymmetric fluid-structure-interaction problem. The fluid is confined in a bounded planar channel and is governed by the stationary Navier-Stokes equations with laminar inflow and…

Analysis of PDEs · Mathematics 2023-08-11 Edoardo Bocchi , Filippo Gazzola

State-dependent parameter identification, where unknown model parameters depend on one or more state variables in partial differential equations (PDEs) or coupled PDE systems, is fundamental to a wide range of problems in physics,…

Optimization and Control · Mathematics 2026-01-19 Vladislav Bukshtynov

We approximate a two--phase model by the compressible Navier-Stokes equations with a singular pressure term. Up to a subsequence, these solutions are shown to converge to a global weak solution of the compressible system with the congestion…

Analysis of PDEs · Mathematics 2014-10-03 Charlotte Perrin , Ewelina Zatorska

In 2001, Bertalmio et. al. drew an analogy between the image intensity function for the image inpainting problem and the stream function in a two-dimensional (2D) incompressible fluid. An approximate solution to the inpainting problem is…

Numerical Analysis · Mathematics 2009-12-15 M. A. Ebrahimi , Michael Holst , Evelyn Lunasin

This thesis contributes to the understanding of symmetry-enriched topological phases focusing on their descriptions in terms of tensor network states. The Projected Entangled Pair State (PEPS) formalism allows us to locally encode the main…

Quantum Physics · Physics 2019-12-19 José Garre-Rubio

This paper proposes an efficient potential and viscous flow decomposition method for wave-structure interaction simulation with single-phase potential flow wave models and two-phase Computational Fluid Dynamics (CFD) solvers. The potential…

In this paper, we study the problem of designing a simultaneous mode, input, and state set-valued observer for a class of hidden mode switched nonlinear systems with bounded-norm noise and unknown input signals, where the hidden mode and…

Systems and Control · Electrical Eng. & Systems 2021-02-23 Mohammad Khajenejad , Sze Zheng Yong

Use of generative models and deep learning for physics-based systems is currently dominated by the task of emulation. However, the remarkable flexibility offered by data-driven architectures would suggest to extend this representation to…

Machine Learning · Computer Science 2023-09-12 Guoxiang Grayson Tong , Carlos A. Sing Long , Daniele E. Schiavazzi

We consider critical eigenstates in a two dimensional quasicrystal and their evolution as a function of disorder. By exact diagonalization of finite size systems we show that the evolution of properties of a typical wave-function is…

Disordered Systems and Neural Networks · Physics 2023-03-08 Anuradha Jagannathan , Marco Tarzia

We consider the numerical approximation of a sharp-interface model for two-phase flow, which is given by the incompressible Navier-Stokes equations in the bulk domain together with the classical interface conditions on the interface. We…

Numerical Analysis · Mathematics 2023-06-21 Harald Garcke , Robert Nürnberg , Quan Zhao

Data assimilation combines information from physical observations and numerical simulation results to obtain better estimates of the state and parameters of a physical system. A wide class of physical systems of interest have solutions that…

Optimization and Control · Mathematics 2025-05-02 Amit N. Subrahmanya , Adrian Sandu

We develop a new method which extends Dynamic Mode Decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems. DMD finds spatial-temporal coherent modes, connects local-linear…

Optimization and Control · Mathematics 2014-09-24 Joshua L. Proctor , Steven L. Brunton , J. Nathan Kutz

A new time discretization scheme for the numerical simulation of two-phase flow governed by a thermodynamically consistent diffuse interface model is presented. The scheme is consistent in the sense that it allows for a discrete in time…

Analysis of PDEs · Mathematics 2014-02-27 Harald Garcke , Michael Hinze , Christian Kahle

This paper addresses the problem of robust process and sensor fault reconstruction for nonlinear systems. The proposed method augments the system dynamics with an approximated internal linear model of the combined contribution of known…

Systems and Control · Electrical Eng. & Systems 2023-04-12 Farhad Ghanipoor , Carlos Murguia , Peyman Mohajerin Esfahani , Nathan van de Wouw

Although image restoration has advanced significantly, most existing methods target only a single type of degradation. In real-world scenarios, images often contain multiple degradations simultaneously, such as rain, noise, and haze,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Hu Gao , Xiaoning Lei , Xichen Xu , Depeng Dang , Lizhuang Ma

The resolvent analysis of McKeon & Sharma (2010) recasts the Navier-Stokes equations into an input/output form in which the nonlinear term is treated as a forcing that acts upon the linear dynamics to yield a velocity response. The…

Fluid Dynamics · Physics 2017-06-01 Kevin Rosenberg , Beverley J. McKeon

Reactions at solid-water interfaces play a foundational role in water treatment systems, catalysis, chemical separations, and in predicting chemical fate and transport in the environment. Over the last century, experimental measurements and…

Chemical Physics · Physics 2022-12-14 Anastasia G. Ilgen , Kevin Leung , Louise J. Criscenti , Jeffery A. Greathouse

Identifiability is central to the interpretability of deep latent variable models, ensuring parameterisations are uniquely determined by the data-generating distribution. However, it remains underexplored for deep regime-switching time…

Machine Learning · Statistics 2026-01-08 Carles Balsells-Rodas , Toshiko Matsui , Pedro A. M. Mediano , Yixin Wang , Yingzhen Li
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