Results 191 to 200 of about 134,557 (305)
Efficient Clustering-based Noise Covariance Estimation for Maximum Noise Fraction. [PDF]
Natl Conf Comput Vis Pattern Recognit Image Process Graph, 2018 Gupta S, Bajaj C.
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
On the estimation of covariance matrices using panel data artificial regressions
, 2003 The use of artificial regressions to compute the variance of the difference of pairs of panel data estimators that cannot be ranked in terms of efficiency is considered.
Patacchini, Eleonora
core
Advanced Intelligent Discovery, EarlyView.Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo +5 more
wiley +1 more source
Evaluating covariance matrix forecasts in a value-at-risk framework [PDF]
Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models, ranging from matrices of simple summary measures to covariance matrices implied from option ...
Christian A. Walter, Jose A. Lopez
core
Advanced Intelligent Discovery, EarlyView.Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Different shades of default mode disturbance in schizophrenia: Subnodal covariance estimation in structure and function. [PDF]
Hum Brain Mapp, 2018 Lefort-Besnard J +11 more
europepmc +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Fast Component Pursuit for Large-Scale Inverse Covariance Estimation. [PDF]
KDD, 2016 Han L, Zhang Y, Zhang T.
europepmc +1 more source
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Advanced Intelligent Discovery, EarlyView.Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source