Results 121 to 130 of about 157,395 (292)
Variational Bayesian EM Algorithm for Quantile Regression in Linear Mixed Effects Models
MathematicsThis paper extends the normal-beta prime (NBP) prior to Bayesian quantile regression in linear mixed effects models and conducts Bayesian variable selection for the fixed effects of the model.
Weixian Wang, Maozai Tian
doaj +1 more source
Bayesian Penalized Method for Streaming Feature Selection
IEEE Access, 2019 The online feature selection with streaming features has become more and more important in recent years. In contrast to standard feature selection method, streaming feature selection method can select feature dynamically without exploring full feature ...
Xiao-Ting Wang, Xin-Ze Luan
doaj +1 more source
Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Bayesian model selection in high-dimensional settings
, 2012 Standard assumptions incorporated into Bayesian model selection procedures result in procedures that are not competitive with commonly used penalized likelihood methods.
Johnson, Valen E., Rossell, David
core +1 more source
CPT: Pharmacometrics & Systems PharmacologyBayesian estimation is a powerful but underutilized tool for answering drug development questions. In this tutorial, the principles of Bayesian model development, assessment, and prior selection will be outlined.
Curtis K. Johnston +5 more
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Spatiotemporal reproduction number with Bayesian model selection for evaluation of emerging infectious disease transmissibility: an application to COVID-19 national surveillance data. [PDF]
BMC Med Res Methodol, 2023 Rotejanaprasert C, Lawson AB, Maude RJ.
europepmc +1 more source
Efficient Bayesian Regularization for Graphical Model Selection
Bayesian Analysis, 2019 There has been an intense development in the Bayesian graphical model literature over the past decade; however, most of the existing methods are restricted to moderate dimensions. We propose a novel graphical model selection approach for large dimensional settings where the dimension increases with the sample size, by decoupling model fitting and ...
Kundu, Suprateek +2 more
openaire +4 more sources
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Triple equivalence for the emergence of biological intelligence
Communications PhysicsIntelligent algorithms developed evolutionarily within neural systems are considered in this work. Mathematical analyses unveil a triple equivalence between canonical neural networks, variational Bayesian inference under a class of partially observable ...
Takuya Isomura
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Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Advanced Materials, EarlyView.Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source