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Whole-slide image analysis via the means of computational pathology often relies on processing tessellated gigapixel images with only slide-level labels available. Applying multiple instance learning-based methods or transformer models is…

Computer Vision and Pattern Recognition · Computer Science 2023-10-20 Joshua Butke , Noriaki Hashimoto , Ichiro Takeuchi , Hiroaki Miyoshi , Koichi Ohshima , Jun Sakuma

Monte Carlo (MC) simulations are powerful computational tools for investigating thermodynamic behavior and validating analytical approaches in complex physical systems. Here we present ETHER (Efficient Tool for THermodynamics Exploration…

Strongly Correlated Electrons · Physics 2026-03-10 Mukesh Kumar Sharma

The MCPlas toolbox represents a collection of MATLAB functions for the automated generation of an equation-based fluid-Poisson model for non-thermal plasmas in the multiphysics simulation software COMSOL. Following the development of the…

Magnetic Resonance Imaging (MRI) provides detailed tissue information, but its clinical application is limited by long acquisition time, high cost, and restricted resolution. Image translation has recently gained attention as a strategy to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Xihe Qiu , Yang Dai , Xiaoyu Tan , Sijia Li , Fenghao Sun , Lu Gan , Liang Liu

We introduce SeeMPS, a Python library dedicated to implementing tensor network algorithms based on the well-known Matrix Product States (MPS) and Quantized Tensor Train (QTT) formalisms. SeeMPS is implemented as a complete finite precision…

This paper puts forth a novel bi-linear modeling framework for data recovery via manifold-learning and sparse-approximation arguments and considers its application to dynamic magnetic-resonance imaging (dMRI). Each temporal-domain MR image…

Image and Video Processing · Electrical Eng. & Systems 2020-02-28 Gaurav N. Shetty , Konstantinos Slavakis , Abhishek Bose , Ukash Nakarmi , Gesualdo Scutari , Leslie Ying

We present SpectralUnmix, an R package for regularized non-negative matrix factorization (NMF), implemented in torch with optional GPU acceleration. The package estimates low-rank non-negative representations through proximal-gradient…

Instrumentation and Methods for Astrophysics · Physics 2026-04-06 Rafael S. de Souza , Paula Coelho , Niranjana P , Ana L. Chies-Santos , Rogério Riffel

As deep neural networks require tremendous amount of computation and memory, analog computing with emerging memory devices is a promising alternative to digital computing for edge devices. However, because of the increasing simulation time…

Machine Learning · Computer Science 2021-01-21 Chaeun Lee , Seyoung Kim

SimTensor is a multi-platform, open-source software for generating artificial tensor data (either with CP/PARAFAC or Tucker structure) for reproducible research on tensor factorization algorithms. SimTensor is a stand-alone application…

Mathematical Software · Computer Science 2016-12-13 Hadi Fanaee-T , Joao Gama

The procedure for simulating the nuclear magnetic resonance spectrum linked to the spin system of a molecule for a certain nucleus entails diagonalizing the associated Hamiltonian matrix. As the dimensions of said matrix grow exponentially…

Quantum Physics · Physics 2024-10-29 Joaquín Ossorio-Castillo , Alexandre Rodríguez-Coello

Metal-organic frameworks (MOFs) offer a vast design space, and as such, computational simulations play a critical role in predicting their structural and physicochemical properties. However, MOF simulations remain difficult to access…

Artificial Intelligence · Computer Science 2026-04-01 Jaewoong Lee , Taeun Bae , Jihan Kim

The present work shows a quantitative trade-off analysis of the Simbol-X Mirror Spacecraft (MSC) passive shielding, in the phase space of the various parameters: mass budget, dimension, geometry, and composition. A simplified physical (and…

Instrumentation and Methods for Astrophysics · Physics 2009-06-25 V. Fioretti , G. Malaguti , A. Bulgarelli , G. G. C. Palumbo , A. Ferri , P. Attina'

Neurosurgery increasingly uses Mixed Reality (MR) technologies for intraoperative assistance. The greatest challenge in this area is mentally reconstructing complex 3D anatomical structures from 2D slices with millimetric precision, which…

In this paper, the intrinsic physical characteristics of spin-orbit torque (SOT) magnetoresistive random-access memory (MRAM) devices are leveraged to realize sigmoidal neurons in neuromorphic architectures. Performance comparisons with the…

Emerging Technologies · Computer Science 2020-06-03 Brendan Reidy , Ramtin Zand

We explore the idea of integrating machine learning (ML) with high performance computing (HPC)-driven simulations to address challenges in using simulations to teach computational science and engineering courses. We demonstrate that a ML…

Physics Education · Physics 2020-09-01 Vikram Jadhao , JCS Kadupitiya

Mixed Reality (MR) is of increasing interest within technology-driven modern medicine but is not yet used in everyday practice. This situation is changing rapidly, however, and this paper explores the emergence of MR technology and the…

Computer Vision and Pattern Recognition · Computer Science 2017-08-04 Long Chen , Thomas Day , Wen Tang , Nigel W. John

A Monte Carlo program which simulates the response of SiPMs is presented. Input to the program are the mean number and the time distribution of Geiger discharges from light, as well as the dark-count rate. For every primary Geiger discharge…

Instrumentation and Detectors · Physics 2020-06-22 E. Garutti , R. Klanner , J. Rolph , J. Schwandt

QCMaquis is a quantum chemistry software package for general molecular structure calculations in a matrix product state/matrix product operator formalism of the density matrix renormalization group (DMRG). It supports a wide range of…

The Simulation Environment for Atomistic and Molecular Modeling (SEAMM) is an open-source software package written in Python that provides a graphical interface for setting up, executing, and analyzing molecular and materials simulations.…

In order to constrain ultra light dark matter models with current and near future weak lensing surveys we need the predictions for the non-linear dark matter power-spectrum. This is commonly extracted from numerical simulations or from…

Cosmology and Nongalactic Astrophysics · Physics 2025-10-15 Dennis Fremstad , Hans A. Winther