Results 141 to 150 of about 7,371,142 (245)
Learning a bayesian network from ordinal data [PDF]
Bayesian networks are graphical models that represent the joint distributionof a set of variables using directed acyclic graphs. When the dependence structure is unknown (or partially known) the network can be learnt from data.
Flaminia Musella
core
Advanced Science, EarlyView.Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Renjian Li +11 more
wiley +1 more source
CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model
Advanced Science, EarlyView.In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang +4 more
wiley +1 more source
Bayesian Inference in Dynamic Disequilibrium Models : an Application to the Polish Credit Market [PDF]
We review Bayesian inference for dynamic latent variable models using the data augmentation principle. We detail the difficulties of stimulating dynamic latent variables in a Gibbs sampler.
Luc, BAUWENS, Michel, LUBRANO
core
Machine Learning of Temperature‐Dependent Chemical Kinetics Using Parallel Droplet Microreactors
Advanced Science, EarlyView.An integrated droplet microfluidics and machine learning framework enables high‐throughput characterization of temperature‐dependent reaction kinetics. Time‐resolved measurements from thousands of droplets train Neural ODE models that accurately predict nonlinear reaction dynamics across diverse thermal environments, bridging large‐scale ...
Mamoru Saita, Yutaka Hori
wiley +1 more source
A dynamic Bayesian network for estimating the risk of falls from real gait data [PDF]
, 2013 Pathological and age-related changes may affect an individual’s gait, in turn raising the risk of falls. In elderly, falls are common and may eventuate in severe injuries, long-term disabilities, and even death.
Eduardo Francisco Morales Manzanares +5 more
core
Drought Stress Mediated Changes in Food Crops: Mechanisms and Remediation Strategies
Advanced Science, EarlyView.This work presents a multi‐scale framework for flavonoid‐mediated drought tolerance in staple food crops, integrating ROS redox regulation, antioxidant defense, rhizosphere microbial interactions, and sustainable agronomic practices. This interdisciplinary model provides core insights to develop climate‐resilient cropping systems and enhance global ...
Xiaoyi Duan +5 more
wiley +1 more source
A dynamic Bayesian network for estimating the risk of falls from real gait data [PDF]
, 2012 Pathological and age-related changes may affect an individual’s gait, in turn raising the risk of falls. In elderly, falls are common and may eventuate in severe injuries, long-term disabilities, and even death.
Eduardo Francisco Morales Manzanares +5 more
core
PLoS ONETo address the limitations of traditional pricing models regarding accuracy and adaptability in high-frequency trading, this study presents a Transformer-based Efficiently-Fused Optimized Bayesian Network (Trans-EFOBN) for financial asset pricing.
Qi Fu, Xiaotong Li
doaj +1 more source
Advanced Science, EarlyView.The protein aggregates and gene expression in the middle temporal gyrus (MTG) and somatosensory cortex (SOM) of the postmortem brains of 13 Alzheimer's disease patients were studied in detail, revealing that small hyperphosphorylated tau aggregates increase with Braak stage driven by microglial inflammation.
Elizabeth A. English +9 more
wiley +1 more source