Results 121 to 130 of about 140,209 (263)
Advanced Intelligent Discovery, EarlyView.A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
Expressions for the covariance matrix of covariance data
, 2009 In several estimation methods used in system identification, a first step is to estimate the covariance functions of the measured inputs and outputs for a small set of lags. These covariance elements can be set up as a vector. The report treats the problem of deriving and computing the asymptotic covariance matrix of this vector, when the number of ...
openaire +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Estimating Quantum Mutual Information of Continuous-Variable Quantum States by Measuring Purity and Covariance Matrix. [PDF]
Entropy (Basel), 2022 Park J.
europepmc +1 more source
Covariance Matrix Adaptation Evolution Strategy without a matrix
Proceedings of the Genetic and Evolutionary Computation Conference CompanionCovariance Matrix Adaptation Evolution Strategy (CMA-ES) is a highly effective optimization technique. A primary challenge when applying CMA-ES in high dimensionality is sampling from a multivariate normal distribution with an arbitrary covariance matrix, which involves its decomposition.
Jarosław Arabas +4 more
openaire +2 more sources
Advanced Experiment Design Strategies for Drug Development
Advanced Intelligent Discovery, EarlyView.Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang +3 more
wiley +1 more source
Minimum variance beamforming combined with covariance matrix-based adaptive weighting for medical ultrasound imaging. [PDF]
Biomed Eng Online, 2022 Wang Y +5 more
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source
Estimation of the Covariance Matrix in Hierarchical Bayesian Spatio-Temporal Modeling via Dimension Expansion. [PDF]
Entropy (Basel), 2022 Sun B, Wu Y.
europepmc +1 more source