Results 81 to 90 of about 529,167 (319)
An Empirical-Bayes Score for Discrete Bayesian Networks
Bayesian network structure learning is often performed in a Bayesian setting, by evaluating candidate structures using their posterior probabilities for a given data set.
Scutari, Marco
core
Consensus Formation and Change are Enhanced by Neutrality
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee +4 more
wiley +1 more source
MODELS AND METHODS FOR IMPLEMENTING PEDAGOGICAL INTERVENTIONS IN MODEL-TRACING COGNITIVE TUTORS
This paper presents some models and methods for generating pedagogical interventions in model-tracing cognitive tutors. They use Bayesian networks for assessment and making decisions, this feature allows managing uncertainty reasoning based on a formal ...
Juan Pablo Martinez Bastida +2 more
doaj +1 more source
Skeleton‐oriented object segmentation (SKOOTS) introduces a new strategy for 3D mitochondrial instance segmentation by predicting explicit skeletons rather than relying on boundary cues. This approach enables robust analysis of densely packed organelles in large FIB‐SEM datasets.
Christopher J. Buswinka +3 more
wiley +1 more source
Spintronic Bayesian Hardware Driven by Stochastic Magnetic Domain Wall Dynamics
Magnetic Probabilistic Computing (MPC) utilizes intrinsic stochastic dynamics in domain walls to establish a hardware foundation for uncertainty‐aware artificial intelligence. Thermally driven domain‐wall fluctuations, voltage‐controlled magnetic anisotropy, and TMR readout enable fully electrical, tunable probabilistic inference.
Tianyi Wang +11 more
wiley +1 more source
Background: Network science as a new field in psychological measurement provides a good platform for test analysis, but in Iran, research on the analysis of test questions using network data analysis has been neglected. Aims: The aim of this study was to
Nadia Soltani +3 more
doaj
SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics
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
Bayesian network modeling method based on case reasoning for emergency decision-making
Bayesian network has the abilities of probability expression, uncertainty management and multi-information fusion.It can support emergency decision-making, which can improve the efficiency of decision-making.Emergency decision-making is highly time ...
XU Lei, LI Xiangyang, YU Minglu
doaj
Bayesian network considering the clustering of the customers in a hair salon
The service industry, which includes hair salons, currently accounts for almost 70% of Japan’s GDP(Gross Domestic Product). Although hair salons are frequently used, over the years, the industry has decreased in size.
Yuki Horita, Haruka Yamashita
doaj +1 more source

