Results 131 to 140 of about 4,500,411 (350)
Assessing Strengths and Limitations of Magnetoencephalography Source Imaging With Intracerebral EEG
Simultaneous MEG and stereotactic EEG (SEEG) recordings provide a direct validation framework for MEG source imaging in focal epilepsy. Virtual SEEG signals derived from MEG reconstructions reveal significant agreement with intracranial measures of spike localization, resting‐state oscillations, and functional connectivity, while also identifying ...
Jawata Afnan +10 more
wiley +1 more source
Bounding entanglement dimensionality from the covariance matrix [PDF]
High-dimensional entanglement has been identified as an important resource in quantum information processing, and also as a main obstacle for simulating quantum systems.
Shuheng Liu +4 more
doaj +1 more source
Knowledge-aided STAP in heterogeneous clutter using a hierarchical bayesian algorithm [PDF]
This paper addresses the problem of estimating the covariance matrix of a primary vector from heterogeneous samples and some prior knowledge, under the framework of knowledge-aided space-time adaptive processing (KA-STAP).
Bidon, Stéphanie +5 more
core +1 more source
A novel exercise‐inducible myokine acidic ribosomal protein P2 (RPLP2), initially identified from human trials, is presented here, whose circulating levels negatively correlate with clinical anxiety severity. Muscle‐derived RPLP2 enhances hippocampal ribosomal assembly and adult neurogenesis to rescue stress‐induced anxiety deficits.
Peiyu Luo +18 more
wiley +1 more source
The K-Step Spatial Sign Covariance Matrix [PDF]
The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is often used as an easy-to-compute and highly robust estimator.
Yadine, A., Croux, C., Dehon, C.
core
HAC estimation in spatial panels [PDF]
© 2012 Elsevier B.V. All rights reservedWe propose a HAC estimator for the covariance matrix of the fixed effects estimator in a panel data model with unobserved fixed effects and errors that are both serially and spatially correlated.conomic and Social ...
tosetti e +5 more
core +1 more source
StackingNet: Collective Inference Across Independent AI Foundation Models
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li +4 more
wiley +1 more source
Improved HAC Covariance Matrix Estimation Based on Forecast Errors [PDF]
We propose computing HAC covariance matrix estimators based on one-stepahead forecasting errors. It is shown that this estimator is consistent and has smaller bias than other HAC estimators.
Yu-Wei Hsieh, Chung-Ming Kuan
core
A Pan‐Methylome Framework for Population‐Scale Bacterial Epigenomics
A scalable quantitative framework unlocks population‐level comparative epigenomics in bacteria. By transforming site‐level data into standardized traits, this approach reconstructs methylation‐informed phylogenies and defines the core epigenome.
Bin Ma +22 more
wiley +1 more source
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park +3 more
wiley +1 more source

