Results 61 to 70 of about 5,496,658 (160)

Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications

Algorithms, 2022
We propose an alternative maximum entropy approach to learning the spectra of massive graphs. In contrast to state-of-the-art Lanczos algorithm for spectral density estimation and applications thereof, our approach does not require kernel smoothing.
Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael Osborne, Stephen Roberts   +5 more
doaj   +1 more source

Nonlinear Kinematic Depth Inversion Coupled With a Spectral Wave Model

Journal of Geophysical Research: Oceans, Volume 131, Issue 8, August 2026.
Abstract We present a bidirectional coupling between a nonlinear kinematic depth inversion method and a phase‐averaged spectral wave model to evaluate the influence of wave nonlinearity over gently sloping nearshore bathymetry. Time‐resolved wave imagery provides spatially varying frequency–wavenumber fields, whereas the simulated significant wave ...
Byunguk Kim, Yong Sung Park, Hyoseob Noh, Seungjun Baek, Juyeong Hur   +4 more
wiley   +1 more source

A staggered eigensolver based on sparse matrix bidiagonalization

EPJ Web of Conferences, 2018
We present a method for calculating eigenvectors of the staggered Dirac operator based on the Golub-Kahan-Lanczos bidiagonalization algorithm. Instead of using orthogonalization during the bidiagonalization procedure to increase stability, we choose to ...
Osborn James C., Jin Xiao-Yong
doaj   +1 more source

Multi-state quantum simulations via model-space quantum imaginary time evolution

npj Quantum Information, 2023
We introduce the framework of model space into quantum imaginary time evolution (QITE) to enable stable estimation of ground and excited states using a quantum computer. Model-space QITE (MSQITE) propagates a model space to the exact one by retaining its
Takashi Tsuchimochi, Yoohee Ryo, Siu Chung Tsang, Seiichiro L. Ten-no   +3 more
doaj   +1 more source

Joint Identification of Groundwater Contamination Source and Heterogeneous Hydrogeological Parameters in LNAPL‐Contaminated Sites Based on Deep Convolutional Encoder‐Decoder Neural Networks

Water Resources Research, Volume 62, Issue 8, August 2026.
Abstract Accurate identification of nonaqueous phase liquid (NAPL) contamination sources is critical in pollution management. However, the joint inversion of source characteristics and heterogeneous hydrogeological parameters faces two major challenges.
Jiannan Luo, Aimin Cai, Xi Ma, Yong Liu, Yefei Ji, Bishan Meng, Wenxi Lu   +6 more
wiley   +1 more source

Latitude‐Dependent Sensitive Areas for Targeted Observations of Mesoscale Eddies Associated With Sea Surface Height Anomaly Forecasts

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract By employing the conditional nonlinear optimal perturbation approach within a two‐layer quasigeostrophic (QG) model, we investigate the sensitive areas for targeted observations of mesoscale eddies relevant to sea surface height anomaly (SSHA) forecasting and reveal their pronounced latitude dependence.
Lin Jiang, Wansuo Duan, Hui Wang
wiley   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

Advanced Materials Technologies, Volume 11, Issue 13, 8 July 2026.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue, Yuan Gao, Fanping Sui, Jason Wang, Megan Teng, Peggy Tsao, Huicong Deng, Yande Peng, Liwei Lin   +8 more
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, Volume 8, Issue 7, July 2026.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Image Super-Resolution Via Wavelet Feature Extraction and Sparse Representation [PDF]

Radioengineering, 2018
This paper proposes a novel Super-Resolution (SR) technique based on wavelet feature extraction and sparse representation. First, the Low-Resolution (LR) image is interpolated employing the Lanczos operation. Then, the image is decomposed into sub-bands (
V. Alvarez-Ramos, V. Ponomaryov, S. Sadovnychiy   +2 more
doaj  

Spot Position Extraction Based on High-resolution Parametric Subspace Method without Eigen decomposition

Wasit Journal of Engineering Sciences, 2013
This paper presents a subspace method of spot centroiding algorithm for locating the centers of laser spots. It focuses on how to find the position of the activated pixel which is the position of the imaged spot on the detector of the camera using ...
Azad Raheem Kareem
doaj   +1 more source