Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...
Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...
TSD 20: Multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints (PDF, 1.2MB) – October 2019 – Updated December 2022: ...
Abstract: The imagery speech (IS) is the speech that the human beings are thinking in their brain. A brain computer interface (BCI) system is employed to translate the speech thinking in the brain to ...
Abstract: In this letter, we propose a multivariable disturbance observer-based finite-time sliding mode attitude control (MDOB-FT-SM-AC) for fixed-wing UAVs in the presence of both matched and ...
We introduce a flexible parametric family of matrix-valued covariance functions for multivariate spatial random fields, where each con stituent component is a Mat rn process. The model parameters are ...
Tito A. Mijares, The Moments of Elementary Symmetric Functions of the Roots of a Matrix in Multivariate Analysis, The Annals of Mathematical Statistics, Vol. 32, No. 4 (Dec., 1961), pp. 1152-1160 ...
A reversible instance normalization layer to normalize individual series. A linear embedding layer that projects individual series into the embedding space. Mamba blocks that capture the correlations ...
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