Results 111 to 120 of about 556,837 (257)
Frontiers in Applied Mathematics and Statistics, 2019 High-dimensional data from molecular biology possess an intricate correlation structure that is imposed by the molecular interactions between genes and their products forming various different types of gene networks.
Frank Emmert-Streib +6 more
doaj +1 more source
Factored sparse inverse covariance matrices [PDF]
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002 Most HMM-based speech recognition systems use Gaussian mixtures as observation probability density functions. An important goal in all such systems is to improve parsimony. One method is to adjust the type of covariance matrices used. In this work, factored sparse inverse covariance matrices are introduced.
openaire +2 more sources
On the estimation of covariance matrices using panel data artificial regressions [PDF]
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
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Advanced Science, EarlyView.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
Journal of High Energy Physics, 2018 The three precision measurements of the cross section σ(e + e − → π + π −γ(γ)) using initial state radiation by the KLOE collaboration provide an important input for the prediction of the hadronic contribution to the anomalous magnetic moment of the muon.
The KLOE-2 collaboration +64 more
doaj +1 more source
Advanced Science, EarlyView.Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais +32 more
wiley +1 more source
Advanced Science, EarlyView.Mice can transfer the learned rule of spatial working memory to guide similar but novel tasks. Hippocampal CA3 populational activity dynamically reorganize during memory generalization, shifting from task‐specific to generalized coding over testing days. Sparse yet redundant neural representations of CA3 enable rule transfer and cognitive map formation,
Da Song +8 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.
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A Panel of Circulating Exosomal sncRNAs Associated With Lung Cancer Risk up to 10 Years in Advance
Advanced Science, EarlyView.Lung cancer is often diagnosed too late, and current screening overlooks many people at risk. In a long‐term study of smokers, a panel of small non‐coding RNAs carried in blood exosomes signals elevated lung cancer risk up to ten years before diagnosis, pointing toward a blood‐based tool for earlier risk detection.
Zhuokun Feng +12 more
wiley +1 more source
Influence function and asymptotic efficiency of the affine equivariant rank covariance matrix. [PDF]
Visuri et al (2001) proposed and illustrated the use of the affine equivariant rank covariance matrix (RCM) in classical multivariate inference problems.
Croux, Christophe, Ollila, E, Oja, H
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