Results 41 to 50 of about 64,158 (253)
Geoscience Letters, 2023 Earthquake occurrence modeling of large subduction events involves significant uncertainty, stemming from the scarcity of geological data and inaccuracy of dating techniques.
Katsuichiro Goda
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Frontiers in Genetics, 2023 To improve the performance of individual DNA sequencing results, researchers often use replicates from the same individual and various statistical clustering models to reconstruct a high-performance callset.
Yue Zhai +16 more
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Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher +10 more
wiley +1 more source
Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani +10 more
wiley +1 more source
An Improved Gaussian Mixture CKF Algorithm under Non-Gaussian Observation Noise
Discrete Dynamics in Nature and Society, 2016 In order to solve the problems that the weight of Gaussian components of Gaussian mixture filter remains constant during the time update stage, an improved Gaussian Mixture Cubature Kalman Filter (IGMCKF) algorithm is designed by combining a Gaussian ...
Hongjian Wang, Cun Li
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PLoS Computational Biology, 2020 Estimating the latent dynamics underlying biological processes is a central problem in computational biology. State-space models with Gaussian statistics are widely used for estimation of such latent dynamics and have been successfully utilized in the ...
Sina Miran +5 more
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On the Influence of Data Imbalance on Supervised Gaussian Mixture Models
Algorithms, 2023 Imbalanced data present a pervasive challenge in many real-world applications of statistical and machine learning, where the instances of one class significantly outnumber those of the other.
Luca Scrucca
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Federated Gaussian Mixture Models
CoRRThis paper introduces FedGenGMM, a novel one-shot federated learning approach for Gaussian Mixture Models (GMM) tailored for unsupervised learning scenarios. In federated learning (FL), where multiple decentralized clients collaboratively train models without sharing raw data, significant challenges include statistical heterogeneity, high communication
Sophia Zhang Pettersson +2 more
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Gaussian Mixture Modeling with Gaussian Process Latent Variable Models [PDF]
, 2010 11 pages, 2 figures, 3 ...
Nickisch, H., Rasmussen, C.
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Anchored Bayesian Gaussian mixture models
Electronic Journal of Statistics, 2020 Finite mixtures are a flexible modeling tool for irregularly shaped densities and samples from heterogeneous populations. When modeling with mixtures using an exchangeable prior on the component features, the component labels are arbitrary and are indistinguishable in posterior analysis.
Kunkel, Deborah, Peruggia, Mario
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