Results 101 to 110 of about 758,750 (320)
SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics
Advanced Science, EarlyView.ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao +11 more
wiley +1 more source
Hierarchical Dynamic Beta Model
Revstat Statistical Journal, 2016 We develop a hierarchical dynamic Bayesian beta model for modelling a set of time series of rates or proportions. The proposed methodology enables to combine the information contained in different time series so that we can describe a common underlying ...
Cibele Queiroz Da-Silva +1 more
doaj +1 more source
Bayesian Nonparametric Hidden Semi-Markov Models
, 2012 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data.
Johnson, Matthew J., Willsky, Alan S.
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Bayesian Semiparametric Hierarchical Empirical Likelihood Spatial Models [PDF]
, 2014 We introduce a general hierarchical Bayesian framework that incorporates a flexible nonparametric data model specification through the use of empirical likelihood methodology, which we term semiparametric hierarchical empirical likelihood (SHEL) models ...
Holan, Scott H. +2 more
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Comment: Bayesian Checking of the Second Levels of Hierarchical Models
, 2007 We discuss the methods of Evans and Moshonov [Bayesian Analysis 1 (2006) 893--914, Bayesian Statistics and Its Applications (2007) 145--159] concerning checking for prior-data conflict and their relevance to the method proposed in this paper. [arXiv:0802.
Evans, M.
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Redefining the Health Risk of Battery Materials Through a Biologically Transformed Metal Mixture
Advanced Science, EarlyView.Inhaled NCM particles undergo lysosomal degradation, releasing complex ion mixtures that induce systemic impact. The impact is determined by a critical balance between antagonistic Ni‐Co interactions and synergistic Mn effects. To capture these complexities in risk assessment, we develop an IAI model, ensuring a more accurate quantitative risk ...
Ze Zhang +11 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Bayesian hierarchical vector autoregressive models for patient-level predictive modeling.
PLoS ONE, 2018 Predicting health outcomes from longitudinal health histories is of central importance to healthcare. Observational healthcare databases such as patient diary databases provide a rich resource for patient-level predictive modeling.
Feihan Lu +4 more
doaj +1 more source
Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin +7 more
wiley +1 more source
parallelMCMCcombine: An R Package for Bayesian Methods for Big Data and Analytics
, 2014 Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size.
Conlon, Erin, Miroshnikov, Alexey
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