Results 121 to 130 of about 147,262 (309)
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
Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang +9 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
Posterior Covariance vs. Analysis Error Covariance in Data Assimilation [PDF]
International audienceThe problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function (analysis). The data contain errors (observation and background errors),
Gejadze, Igor +2 more
core
Exceptional Antimodes in Multi‐Drive Cavity Magnonics
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith +4 more
wiley +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
One of the major topics of concern in Modern Portfolio Theory is portfolio optimization which is centred on the mean-variance framework. In order for this framework to be implemented, esti- mated parameters (covariance matrix for the constrained portfo ...
Madume, Jaison Pezisai
core
ABSTRACT This study investigates the impact of geographical indication (GI) certification on the export performance of Turkish agri‐food products by analyzing both trade volume and unit value dynamics. Drawing on monthly data from 2000 to 2024 across 22 GI‐certified products, the research employs product‐level regressions, fixed‐effects panel models ...
Ihlas Sovbetov, Muge Burcu Ozdemir
wiley +1 more source
Abstract Nucleus outgrower schemes are contractual arrangements where well‐resourced large‐scale farmers (nucleus farmers) are empowered by development support agencies to take charge of smallholder farmers, by providing them with market access and the necessary training on agronomic practices and farm inputs for production.
Dominic Tasila Konja, Awudu Abdulai
wiley +1 more source
Low-dimensional Representation of Error Covariance
Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to ...
Marchesin, Dan +3 more
core +1 more source

