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Multilayered poroelastic structures are found in many biological tissues such as cartilage and the cornea, and play a key role in the design of bioartificial organs and other bioengineering applications. Motivated by these applications, we…

Numerical Analysis · Mathematics 2025-07-15 Andrew Scharf , Martina Bukač , Sunčica Čanić

Real world networks are often subject to severe uncertainties which need to be addressed by any reliable prescriptive model. In the context of the maximum flow problem subject to arc failure, robust models have gained particular attention.…

Discrete Mathematics · Computer Science 2017-05-24 Fabian Mies , Britta Peis , Andreas Wierz

When modeling such phenomena as population dynamics, controllable ows, etc., a problem arises of adapting the existing models to a phenomenon under study. For this purpose, we propose to derive new models from the rst principles by…

Symbolic Computation · Computer Science 2018-05-09 D. S. Kulyabov , M. N. Gevorkyan , A. V. Demidova , T. R. Velieva , A. V. Korolkova , L. A. Sevastianov

The general system of images for regularized Stokeslets (GSIRS) developed by Cortez and Varela (2015) is used extensively to model Stokes flow phenomena such as microorganisms swimming near a boundary. Our collaborative team uses…

In this work, we study shape optimization problems in the Stokes flows. By phase-field approaches, the resulted total objective function consists of the dissipation energy of the fluids and the Ginzburg--Landau energy functional as a…

Numerical Analysis · Mathematics 2022-07-13 Futuan Li , Jiang Yang

The developments over the last five decades concerning numerical discretisations of the incompressible Navier--Stokes equations have lead to reliable tools for their approximation: those include stable methods to properly address the…

Numerical Analysis · Mathematics 2025-08-12 Dominic Breit , Andreas Prohl , Jörn Wichmann

The paper generalizes the construction by stochastic flows of consistent utility processes introduced by M. Mrad and N. El Karoui in (2010). The utilities random fields are defined from a general class of processes denoted by $\GX$. Making…

Computational Finance · Quantitative Finance 2013-04-08 N. El Karoui , Mohamed M'Rad

Each training step for a variational autoencoder (VAE) requires us to sample from the approximate posterior, so we usually choose simple (e.g. factorised) approximate posteriors in which sampling is an efficient computation that fully…

Machine Learning · Statistics 2018-05-29 Laurence Aitchison , Vincent Adam , Srinivas C. Turaga

Spatial transcriptomics (ST) has emerged as a powerful technology for bridging histology imaging with gene expression profiling. However, its application has been limited by low throughput and the need for specialized experimental…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Tinglin Huang , Tianyu Liu , Mehrtash Babadi , Wengong Jin , Rex Ying

Collectively coordinated cell migration plays a role in tissue embryogenesis, cancer, homeostasis and healing. To study these processes, different cell-based modelling approaches have been developed, ranging from lattice-based cellular…

Soft Condensed Matter · Physics 2023-05-19 Carine P. Beatrici , Cassio A. Kirch , Silke Henkes , François Graner , Leonardo G. Brunnet

The manipulation of a collection of fluid particles in a low Reynolds number environment has several important applications. As we demonstrate in this paper, this manipulation problem is related to the scientific question of how fluid flow…

Fluid Dynamics · Physics 2024-02-27 Jake Buzhardt , Phanindra Tallapragada

Flow matching is a scalable generative framework for characterizing continuous normalizing flows with wide-range applications. However, current state-of-the-art methods are not well-suited for modeling dynamical systems, as they construct…

Machine Learning · Computer Science 2026-05-15 Santanu Subhash Rathod , Pietro Liò , Xiao Zhang

The transport of bio-particles in viscous flows exhibits a rich variety of dynamical behaviour, such as morphological transitions, complex orientation dynamics or deformations. Characterising such complex behaviour under well controlled…

We propose a GPU-accelerated distributed optimization algorithm for controlling multi-phase optimal power flow in active distribution systems with dynamically changing topologies. To handle varying network configurations and enable…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-15 Minseok Ryu , Geunyeong Byeon , Kibaek Kim

Parallelization of A* path planning is mostly limited by the number of possible motions, which is far less than the level of parallelism that modern processors support. In this paper, we go beyond the limitations of traditional parallelism…

Robotics · Computer Science 2021-02-16 Mohammad Bakhshalipour , Mohamad Qadri , Dominic Guri

An extension of the Method of Regularized Stokeslets (MRS) in three dimensions is developed for triangulated surfaces with a piecewise linear force distribution. The method extends the regularized Stokeslet segment methodology used for…

Numerical Analysis · Mathematics 2024-11-05 Dana Ferranti , Ricardo Cortez

Stochastic Spatio-Temporal processes are prevalent across domains ranging from modeling of plasma to the turbulence in fluids to the wave function of quantum systems. This letter studies a measure-theoretic description of such systems by…

Optimization and Control · Mathematics 2021-05-25 George I. Boutselis , Ethan N. Evans , Marcus A. Pereira , Evangelos A. Theodorou

Nature has evolved many molecular machines such as kinesin, myosin, and the rotary flagellar motor powered by an ion current from the mitochondria. Direct observation of the step-like motion of these machines with time series from novel…

Quantitative Methods · Quantitative Biology 2010-03-30 Max A. Little , Nick S. Jones

To overcome topological constraints and improve the expressiveness of normalizing flow architectures, Wu, K\"ohler and No\'e introduced stochastic normalizing flows which combine deterministic, learnable flow transformations with stochastic…

Machine Learning · Computer Science 2022-12-02 Paul Hagemann , Johannes Hertrich , Gabriele Steidl

We present a versatile high-level programming-language implementation of nonlinear topology optimization. Our implementation is based on the commercial software package Femlab, and it allows a wide range of optimization objectives to be…

Fluid Dynamics · Physics 2007-05-23 Laurits H. Olesen , Fridolin Okkels , Henrik Bruus
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