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We continue studies of the uncertainty quantification problem in emission tomographies such as PET or SPECT when additional multimodal data (e.g., anatomical MRI images) are available. To solve the aforementioned problem we adapt the…

Machine Learning · Statistics 2021-12-03 Fedor Goncharov , Éric Barat , Thomas Dautremer

Due to rapid data growth, statistical analysis of massive datasets often has to be carried out in a distributed fashion, either because several datasets stored in separate physical locations are all relevant to a given problem, or simply to…

Computation · Statistics 2016-02-08 Matthias Katzfuss , Dorit Hammerling

The state of the art for physical hazard prediction from weather and climate requires expensive km-scale numerical simulations driven by coarser resolution global inputs. Here, a generative diffusion architecture is explored for downscaling…

In this paper, we consider an approach to the parallelizing of the algorithms realizing the modified probability changigng method with adaptation and partial rollback procedure for constrained pseudo-Boolean optimization problems. Existing…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-09-03 Lev Kazakovtsev

The Multi-conjugate Adaptive Optics RelaY (MAORY) is one of the key Adaptive Optics (AO) systems on the European Southern Observatory's Extremely Large Telescope. MAORY aims to achieve a good wavefront correction over a large field of view,…

Instrumentation and Methods for Astrophysics · Physics 2022-02-25 Bernadett Stadler , Ronny Ramlau

This work aims to design a distributed extended object tracking (EOT) system over a realistic network, where both the extent and kinematics are required to retain consensus within the entire network. To this end, we resort to the…

Systems and Control · Electrical Eng. & Systems 2022-10-06 Zhifei Li , Yan Liang , Linfeng Xu , Shuli Ma

The accurate prediction of oceanographic variables is crucial for understanding climate change, managing marine resources, and optimizing maritime activities. Traditional ocean forecasting relies on numerical models; however, these…

Machine Learning · Computer Science 2025-10-30 Víctor Medina , Giovanny A. Cuervo-Londoño , Javier Sánchez

Sampling Boltzmann probability distributions plays a key role in machine learning and optimization, motivating the design of hardware accelerators such as Ising machines. While the Ising model can in principle encode arbitrary optimization…

Machine Learning · Computer Science 2025-08-01 Corentin Delacour , M Mahmudul Hasan Sajeeb , Joao P. Hespanha , Kerem Y. Camsari

Event-based image sensors provide microsecond temporal resolution but lack spectral discrimination, whereas diffractive spectral imagers encode wavelength information at conventional frame rates. We introduce a fluorescence microscopy…

Optics · Physics 2026-03-20 Richard G. Baird , Boyden Myers , Erik M. Jorgensen , Rajesh Menon

A new generation of interferometric instruments is emerging which aim to use intensity mapping of redshifted $21\,$cm radiation to measure the large-scale structure of the Universe at $z\simeq 1-2$ over wide areas of sky. While these…

Cosmology and Nongalactic Astrophysics · Physics 2017-08-16 Martin White , Nikhil Padmanabhan

The paper deals with the developing of the methodological backgrounds for the modeling and simulation of complex dynamical objects. Such backgrounds allow us to perform coordinate transformation and formulate the algorithm of its usage for…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-07 Roman Voliansky , Andri Pranolo

We discuss the scalable parallel solution of the Poisson equation within a Particle-In-Cell (PIC) code for the simulation of electron beams in particle accelerators of irregular shape. The problem is discretized by Finite Differences.…

Computational Physics · Physics 2010-04-21 A. Adelmann , P. Arbenz , Y. Ineichen

High resolution simulations of polar ice-sheets play a crucial role in the ongoing effort to develop more accurate and reliable Earth-system models for probabilistic sea-level projections. These simulations often require a massive amount of…

Computational Engineering, Finance, and Science · Computer Science 2022-04-12 Jerry Watkins , Max Carlson , Kyle Shan , Irina Tezaur , Mauro Perego , Luca Bertagna , Carolyn Kao , Matthew J. Hoffman , Stephen F. Price

Full Waveform Inversion (FWI) stands as a nonlinear, high-resolution technology for subsurface imaging via surface-recorded data. This paper introduces an augmented Lagrangian dual formulation for FWI, rooted in the viewpoint that Lagrange…

Geophysics · Physics 2024-12-13 Kamal Aghazade , Ali Gholami

We present a computational algorithm for computing short range forces between particles. The algorithm has two distinguishing features. First, it is optimized for multi-processor computers, and will use as many processors as are available.…

Astrophysics · Physics 2008-02-03 Robert C. Ferrell , Edmund Bertschinger

This paper deals with the numerical modeling of wave propagation in porous media described by Biot's theory. The viscous efforts between the fluid and the elastic skeleton are assumed to be a linear function of the relative velocity, which…

Fluid Dynamics · Physics 2015-05-20 Guillaume Chiavassa , Bruno Lombard

In view of the existing limitations of sequential computing, parallelization has emerged as an alternative in order to improve the speedup of numerical simulations. In the framework of evolutionary problems, space-time parallel methods…

Numerical Analysis · Mathematics 2025-02-13 Andrés Arrarás , Francisco J. Gaspar , Iñigo Jimenez-Ciga , Laura Portero

In this work we propose an efficient and accurate multi-scale optical simulation algorithm by applying a numerical version of slowly varying envelope approximation in FEM. Specifically, we employ the fast iterative method to quickly compute…

Optics · Physics 2024-12-03 Fan Xiao , Jingwei Wang , Zhongfei Xiong , Yuntian Chen

Inverse design of metasurfaces for the joint optimization of optical modulation and algorithmic decoding in computational optics presents significant challenges, especially in applications such as hyperspectral imaging. We introduce a…

Image and Video Processing · Electrical Eng. & Systems 2025-10-28 Rongzhou Chen , Haitao Nie , Shuo Zhu , Yaping Zhao , Chutian Wang , Edmund Y. Lam

High-dimensional data clustering has become and remains a challenging task for modern statistics and machine learning, with a wide range of applications. We consider in this work the powerful discriminative latent mixture model, and we…

Methodology · Statistics 2020-12-09 Nicolas Jouvin , Charles Bouveyron , Pierre Latouche
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